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name="searchtype"><option value="all">All fields</option><option value="title">Title</option><option selected value="author">Author(s)</option><option value="abstract">Abstract</option><option value="comments">Comments</option><option value="journal_ref">Journal reference</option><option value="acm_class">ACM classification</option><option value="msc_class">MSC classification</option><option value="report_num">Report number</option><option value="paper_id">arXiv identifier</option><option value="doi">DOI</option><option value="orcid">ORCID</option><option value="license">License (URI)</option><option value="author_id">arXiv author ID</option><option value="help">Help pages</option><option value="full_text">Full text</option></select> <input id="query" name="query" type="text" value="Lan, J"> <ul id="abstracts"><li><input checked id="abstracts-0" name="abstracts" type="radio" value="show"> <label for="abstracts-0">Show abstracts</label></li><li><input id="abstracts-1" name="abstracts" type="radio" value="hide"> <label for="abstracts-1">Hide abstracts</label></li></ul> </div> <div class="box field is-grouped is-grouped-multiline level-item"> <div class="control"> <span class="select is-small"> <select id="size" name="size"><option value="25">25</option><option selected value="50">50</option><option value="100">100</option><option value="200">200</option></select> </span> <label for="size">results per page</label>. </div> <div class="control"> <label for="order">Sort results by</label> <span class="select is-small"> <select id="order" name="order"><option selected value="-announced_date_first">Announcement date (newest first)</option><option value="announced_date_first">Announcement date (oldest first)</option><option value="-submitted_date">Submission date (newest first)</option><option value="submitted_date">Submission date (oldest first)</option><option value="">Relevance</option></select> </span> </div> <div class="control"> <button class="button is-small is-link">Go</button> </div> </div> </form> </div> </div> <ol class="breathe-horizontal" start="1"> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.13624">arXiv:2409.13624</a> <span> [<a href="https://arxiv.org/pdf/2409.13624">pdf</a>, <a href="https://arxiv.org/format/2409.13624">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Safe stabilization using generalized Lyapunov barrier function </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a>, <a href="/search/eess?searchtype=author&query=van+Henten%2C+E">Eldert van Henten</a>, <a href="/search/eess?searchtype=author&query=Koerkamp%2C+P+G">Peter Groot Koerkamp</a>, <a href="/search/eess?searchtype=author&query=Sun%2C+C">Congcong Sun</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.13624v3-abstract-short" style="display: inline;"> This paper addresses the safe stabilization problem, focusing on controlling the system state to the origin while avoiding entry into unsafe state sets. The current methods for solving this issue rely on smooth Lyapunov and barrier functions, which do not always ensure the existence of an effective controller even when such smooth functions are created. To tackle this challenge, we introduce the c… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.13624v3-abstract-full').style.display = 'inline'; document.getElementById('2409.13624v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.13624v3-abstract-full" style="display: none;"> This paper addresses the safe stabilization problem, focusing on controlling the system state to the origin while avoiding entry into unsafe state sets. The current methods for solving this issue rely on smooth Lyapunov and barrier functions, which do not always ensure the existence of an effective controller even when such smooth functions are created. To tackle this challenge, we introduce the concept of a generalized (nonsmooth) Lyapunov barrier function (GenLBF), which guarantees the existence of a safe and stable controller. We outline a systematic approach for constructing a GenLBF, including a technique for efficiently calculating the upper generalized derivative of the GenLBF. Using the constructed GenLBF, we propose a method for certifying safe stabilization of autonomous systems and design a piecewise continuous feedback control to achieve safe stabilization of non-autonomous systems. A general controller refinement strategy is further proposed to help the state trajectory escape from undesired local points occurring in systems with special physical structure. A thorough theoretical analysis demonstrates the effectiveness of our method in addressing the safe stabilization problem for systems with single or multiple bounded unsafe state sets. Extensive simulations of linear and nonlinear systems further illustrate the efficacy of the proposed method and its superiority over the smooth control Lyapunov barrier function method. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.13624v3-abstract-full').style.display = 'none'; document.getElementById('2409.13624v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 October, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 20 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">19 pages, 14 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.10098">arXiv:2409.10098</a> <span> [<a href="https://arxiv.org/pdf/2409.10098">pdf</a>, <a href="https://arxiv.org/ps/2409.10098">ps</a>, <a href="https://arxiv.org/format/2409.10098">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Emerging Technologies">cs.ET</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Optimization and Control">math.OC</span> </div> </div> <p class="title is-5 mathjax"> An integrated design of robust decentralized observer and controller for load frequency control </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zhao%2C+X">Xianxian Zhao</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.10098v1-abstract-short" style="display: inline;"> This paper focuses on designing completely decentralized load frequency control (LFC) for multi-area power systems to achieve global optimized performance. To this end, a new concept of integrated design is introduced for designing the decentralized LFC observers and controllers simultaneously off-line, by taking into account of the interactions between areas and the bidirectional effects between… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.10098v1-abstract-full').style.display = 'inline'; document.getElementById('2409.10098v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.10098v1-abstract-full" style="display: none;"> This paper focuses on designing completely decentralized load frequency control (LFC) for multi-area power systems to achieve global optimized performance. To this end, a new concept of integrated design is introduced for designing the decentralized LFC observers and controllers simultaneously off-line, by taking into account of the interactions between areas and the bidirectional effects between the local observer and controller in each area. The integrated design in this paper is realized via $H_\infty$ optimization with a single-step linear matrix inequality (LMI) formulation. The LMI regional eigenvalue assignment technique is further incorporated with $H_\infty$ optimization to improve the closed-loop system transient performance. A three-area power system is simulated to validate the superiority of the proposed integrated design over the conventional decentralized designs. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.10098v1-abstract-full').style.display = 'none'; document.getElementById('2409.10098v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">23 pages, 8 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2408.11582">arXiv:2408.11582</a> <span> [<a href="https://arxiv.org/pdf/2408.11582">pdf</a>, <a href="https://arxiv.org/format/2408.11582">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Enhanced Visual SLAM for Collision-free Driving with Lightweight Autonomous Cars </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lin%2C+Z">Zhihao Lin</a>, <a href="/search/eess?searchtype=author&query=Tian%2C+Z">Zhen Tian</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+Q">Qi Zhang</a>, <a href="/search/eess?searchtype=author&query=Zhuang%2C+H">Hanyang Zhuang</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2408.11582v1-abstract-short" style="display: inline;"> The paper presents a vision-based obstacle avoidance strategy for lightweight self-driving cars that can be run on a CPU-only device using a single RGB-D camera. The method consists of two steps: visual perception and path planning. The visual perception part uses ORBSLAM3 enhanced with optical flow to estimate the car's poses and extract rich texture information from the scene. In the path planni… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.11582v1-abstract-full').style.display = 'inline'; document.getElementById('2408.11582v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.11582v1-abstract-full" style="display: none;"> The paper presents a vision-based obstacle avoidance strategy for lightweight self-driving cars that can be run on a CPU-only device using a single RGB-D camera. The method consists of two steps: visual perception and path planning. The visual perception part uses ORBSLAM3 enhanced with optical flow to estimate the car's poses and extract rich texture information from the scene. In the path planning phase, we employ a method combining a control Lyapunov function and control barrier function in the form of quadratic program (CLF-CBF-QP) together with an obstacle shape reconstruction process (SRP) to plan safe and stable trajectories. To validate the performance and robustness of the proposed method, simulation experiments were conducted with a car in various complex indoor environments using the Gazebo simulation environment. Our method can effectively avoid obstacles in the scenes. The proposed algorithm outperforms benchmark algorithms in achieving more stable and shorter trajectories across multiple simulated scenes. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.11582v1-abstract-full').style.display = 'none'; document.getElementById('2408.11582v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">16 pages; Submitted to a journal</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2408.08242">arXiv:2408.08242</a> <span> [<a href="https://arxiv.org/pdf/2408.08242">pdf</a>, <a href="https://arxiv.org/ps/2408.08242">ps</a>, <a href="https://arxiv.org/format/2408.08242">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> A Conflicts-free, Speed-lossless KAN-based Reinforcement Learning Decision System for Interactive Driving in Roundabouts </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lin%2C+Z">Zhihao Lin</a>, <a href="/search/eess?searchtype=author&query=Tian%2C+Z">Zhen Tian</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+Q">Qi Zhang</a>, <a href="/search/eess?searchtype=author&query=Ye%2C+Z">Ziyang Ye</a>, <a href="/search/eess?searchtype=author&query=Zhuang%2C+H">Hanyang Zhuang</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2408.08242v1-abstract-short" style="display: inline;"> Safety and efficiency are crucial for autonomous driving in roundabouts, especially in the context of mixed traffic where autonomous vehicles (AVs) and human-driven vehicles coexist. This paper introduces a learning-based algorithm tailored to foster safe and efficient driving behaviors across varying levels of traffic flows in roundabouts. The proposed algorithm employs a deep Q-learning network… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.08242v1-abstract-full').style.display = 'inline'; document.getElementById('2408.08242v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.08242v1-abstract-full" style="display: none;"> Safety and efficiency are crucial for autonomous driving in roundabouts, especially in the context of mixed traffic where autonomous vehicles (AVs) and human-driven vehicles coexist. This paper introduces a learning-based algorithm tailored to foster safe and efficient driving behaviors across varying levels of traffic flows in roundabouts. The proposed algorithm employs a deep Q-learning network to effectively learn safe and efficient driving strategies in complex multi-vehicle roundabouts. Additionally, a KAN (Kolmogorov-Arnold network) enhances the AVs' ability to learn their surroundings robustly and precisely. An action inspector is integrated to replace dangerous actions to avoid collisions when the AV interacts with the environment, and a route planner is proposed to enhance the driving efficiency and safety of the AVs. Moreover, a model predictive control is adopted to ensure stability and precision of the driving actions. The results show that our proposed system consistently achieves safe and efficient driving whilst maintaining a stable training process, as evidenced by the smooth convergence of the reward function and the low variance in the training curves across various traffic flows. Compared to state-of-the-art benchmarks, the proposed algorithm achieves a lower number of collisions and reduced travel time to destination. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.08242v1-abstract-full').style.display = 'none'; document.getElementById('2408.08242v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">15 pages, 12 figures, submitted to an IEEE journal</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2408.01256">arXiv:2408.01256</a> <span> [<a href="https://arxiv.org/pdf/2408.01256">pdf</a>, <a href="https://arxiv.org/format/2408.01256">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Rate Maximization for RIS-Assisted OAM Multiuser Wireless Communications </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jun Lan</a>, <a href="/search/eess?searchtype=author&query=Liang%2C+L">Liping Liang</a>, <a href="/search/eess?searchtype=author&query=Cheng%2C+W">Wenchi Cheng</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+W">Wei Zhang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2408.01256v1-abstract-short" style="display: inline;"> Conventional multiple-input multiple-out (MIMO) technologies have encountered bottlenecks of significantly increasing spectrum efficiencies of wireless communications due to the low degrees of freedom in practical line-of-sight scenarios and severe path loss of high frequency carriers. Orbital angular momentum (OAM) has shown the potential for high spectrum efficiencies in radio frequency domains.… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.01256v1-abstract-full').style.display = 'inline'; document.getElementById('2408.01256v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.01256v1-abstract-full" style="display: none;"> Conventional multiple-input multiple-out (MIMO) technologies have encountered bottlenecks of significantly increasing spectrum efficiencies of wireless communications due to the low degrees of freedom in practical line-of-sight scenarios and severe path loss of high frequency carriers. Orbital angular momentum (OAM) has shown the potential for high spectrum efficiencies in radio frequency domains. To investigate the advantage of OAM in multiuser communications, in this paper we propose the reconfigurable intelligence surface (RIS) assisted OAM multiuser (MU) wireless communication schemes, where RIS is deployed to establish the direct links blocked by obstacles between the OAM transmitter and users, to significantly increase the achievable sum rate (ASR) of MU systems. To maximize the ASR, we develop the alternative optimization algorithm to jointly optimize the transmit power and phase shifts of RIS. The numerical outcomes demonstrate the superiority of our proposed scheme compared to existing methods in terms of ASR. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.01256v1-abstract-full').style.display = 'none'; document.getElementById('2408.01256v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">5 pages, 5 figures and accepted by UCom 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2407.16158">arXiv:2407.16158</a> <span> [<a href="https://arxiv.org/pdf/2407.16158">pdf</a>, <a href="https://arxiv.org/format/2407.16158">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Cross-Domain Separable Translation Network for Multimodal Image Change Detection </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zhan%2C+T">Tao Zhan</a>, <a href="/search/eess?searchtype=author&query=Zhu%2C+Y">Yuanyuan Zhu</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jie Lan</a>, <a href="/search/eess?searchtype=author&query=Dang%2C+Q">Qianlong Dang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2407.16158v1-abstract-short" style="display: inline;"> In the remote sensing community, multimodal change detection (MCD) is particularly critical due to its ability to track changes across different imaging conditions and sensor types, making it highly applicable to a wide range of real-world scenarios. This paper focuses on addressing the challenges of MCD, especially the difficulty in comparing images from different sensors with varying styles and… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.16158v1-abstract-full').style.display = 'inline'; document.getElementById('2407.16158v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2407.16158v1-abstract-full" style="display: none;"> In the remote sensing community, multimodal change detection (MCD) is particularly critical due to its ability to track changes across different imaging conditions and sensor types, making it highly applicable to a wide range of real-world scenarios. This paper focuses on addressing the challenges of MCD, especially the difficulty in comparing images from different sensors with varying styles and statistical characteristics of geospatial objects. Traditional MCD methods often struggle with these variations, leading to inaccurate and unreliable results. To overcome these limitations, a novel unsupervised cross-domain separable translation network (CSTN) is proposed, which uniquely integrates a within-domain self-reconstruction and a cross-domain image translation and cycle-reconstruction workflow with change detection constraints. The model is optimized by implementing both the tasks of image translation and MCD simultaneously, thereby guaranteeing the comparability of learned features from multimodal images. Specifically, a simple yet efficient dual-branch convolutional architecture is employed to separate the content and style information of multimodal images. This process generates a style-independent content-comparable feature space, which is crucial for achieving accurate change detection even in the presence of significant sensor variations. Extensive experimental results demonstrate the effectiveness of the proposed method, showing remarkable improvements over state-of-the-art approaches in terms of accuracy and efficacy for MCD. The implementation of our method will be publicly available at \url{https://github.com/OMEGA-RS/CSTN} <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2407.16158v1-abstract-full').style.display = 'none'; document.getElementById('2407.16158v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 July, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This work has been submitted to the IEEE for possible publication</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.10372">arXiv:2405.10372</a> <span> [<a href="https://arxiv.org/pdf/2405.10372">pdf</a>, <a href="https://arxiv.org/format/2405.10372">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Optimization and Control">math.OC</span> </div> </div> <p class="title is-5 mathjax"> Efficient model predictive control for nonlinear systems modelled by deep neural networks </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2405.10372v1-abstract-short" style="display: inline;"> This paper presents a model predictive control (MPC) for dynamic systems whose nonlinearity and uncertainty are modelled by deep neural networks (NNs), under input and state constraints. Since the NN output contains a high-order complex nonlinearity of the system state and control input, the MPC problem is nonlinear and challenging to solve for real-time control. This paper proposes two types of m… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.10372v1-abstract-full').style.display = 'inline'; document.getElementById('2405.10372v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.10372v1-abstract-full" style="display: none;"> This paper presents a model predictive control (MPC) for dynamic systems whose nonlinearity and uncertainty are modelled by deep neural networks (NNs), under input and state constraints. Since the NN output contains a high-order complex nonlinearity of the system state and control input, the MPC problem is nonlinear and challenging to solve for real-time control. This paper proposes two types of methods for solving the MPC problem: the mixed integer programming (MIP) method which produces an exact solution to the nonlinear MPC, and linear relaxation (LR) methods which generally give suboptimal solutions but are much computationally cheaper. Extensive numerical simulation for an inverted pendulum system modelled by ReLU NNs of various sizes is used to demonstrate and compare performance of the MIP and LR methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.10372v1-abstract-full').style.display = 'none'; document.getElementById('2405.10372v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 16 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">8 pages, 5 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2404.13456">arXiv:2404.13456</a> <span> [<a href="https://arxiv.org/pdf/2404.13456">pdf</a>, <a href="https://arxiv.org/format/2404.13456">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Real-Time Safe Control of Neural Network Dynamic Models with Sound Approximation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Hu%2C+H">Hanjiang Hu</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a>, <a href="/search/eess?searchtype=author&query=Liu%2C+C">Changliu Liu</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2404.13456v2-abstract-short" style="display: inline;"> Safe control of neural network dynamic models (NNDMs) is important to robotics and many applications. However, it remains challenging to compute an optimal safe control in real time for NNDM. To enable real-time computation, we propose to use a sound approximation of the NNDM in the control synthesis. In particular, we propose Bernstein over-approximated neural dynamics (BOND) based on the Bernste… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.13456v2-abstract-full').style.display = 'inline'; document.getElementById('2404.13456v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2404.13456v2-abstract-full" style="display: none;"> Safe control of neural network dynamic models (NNDMs) is important to robotics and many applications. However, it remains challenging to compute an optimal safe control in real time for NNDM. To enable real-time computation, we propose to use a sound approximation of the NNDM in the control synthesis. In particular, we propose Bernstein over-approximated neural dynamics (BOND) based on the Bernstein polynomial over-approximation (BPO) of ReLU activation functions in NNDM. To mitigate the errors introduced by the approximation and to ensure persistent feasibility of the safe control problems, we synthesize a worst-case safety index using the most unsafe approximated state within the BPO relaxation of NNDM offline. For the online real-time optimization, we formulate the first-order Taylor approximation of the nonlinear worst-case safety constraint as an additional linear layer of NNDM with the l2 bounded bias term for the higher-order remainder. Comprehensive experiments with different neural dynamics and safety constraints show that with safety guaranteed, our NNDMs with sound approximation are 10-100 times faster than the safe control baseline that uses mixed integer programming (MIP), validating the effectiveness of the worst-case safety index and scalability of the proposed BOND in real-time large-scale settings. The code is available at https://github.com/intelligent-control-lab/BOND. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2404.13456v2-abstract-full').style.display = 'none'; document.getElementById('2404.13456v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 20 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 20 April, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Camera-ready version of L4DC 2024, 12 pages, 3 figures, 4 tables</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2403.16136">arXiv:2403.16136</a> <span> [<a href="https://arxiv.org/pdf/2403.16136">pdf</a>, <a href="https://arxiv.org/ps/2403.16136">ps</a>, <a href="https://arxiv.org/format/2403.16136">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Data-Driven Sliding Mode Control for Partially Unknown Nonlinear Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a>, <a href="/search/eess?searchtype=author&query=Zhao%2C+X">Xianxian Zhao</a>, <a href="/search/eess?searchtype=author&query=Sun%2C+C">Congcong Sun</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2403.16136v1-abstract-short" style="display: inline;"> This paper introduces a new design method for data-driven control of nonlinear systems with partially unknown dynamics and unknown bounded disturbance. Since it is not possible to achieve exact nonlinearity cancellation in the presence of unknown disturbance, this paper adapts the idea of sliding mode control (SMC) to ensure system stability and robustness without assuming that the nonlinearity go… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.16136v1-abstract-full').style.display = 'inline'; document.getElementById('2403.16136v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2403.16136v1-abstract-full" style="display: none;"> This paper introduces a new design method for data-driven control of nonlinear systems with partially unknown dynamics and unknown bounded disturbance. Since it is not possible to achieve exact nonlinearity cancellation in the presence of unknown disturbance, this paper adapts the idea of sliding mode control (SMC) to ensure system stability and robustness without assuming that the nonlinearity goes to zero faster than the state as in the existing methods. The SMC consists of a data-dependent robust controller ensuring the system state trajectory reach and remain on the sliding surface and a nominal controller solved from a data-dependent semidefinite program (SDP) ensuring robust stability of the state trajectory on the sliding surface. Numerical simulation results demonstrate effectiveness of the proposed data-driven SMC and its superior in terms of robust stability over the existing data-driven control that also uses approximate nonlinearity cancellation. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.16136v1-abstract-full').style.display = 'none'; document.getElementById('2403.16136v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 March, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Submitted to IEEE CDC 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2403.16132">arXiv:2403.16132</a> <span> [<a href="https://arxiv.org/pdf/2403.16132">pdf</a>, <a href="https://arxiv.org/ps/2403.16132">ps</a>, <a href="https://arxiv.org/format/2403.16132">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Runtime Monitoring and Fault Detection for Neural Network-Controlled Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a>, <a href="/search/eess?searchtype=author&query=Zhan%2C+S">Siyuan Zhan</a>, <a href="/search/eess?searchtype=author&query=Patton%2C+R">Ron Patton</a>, <a href="/search/eess?searchtype=author&query=Zhao%2C+X">Xianxian Zhao</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2403.16132v1-abstract-short" style="display: inline;"> There is an emerging trend in applying deep learning methods to control complex nonlinear systems. This paper considers enhancing the runtime safety of nonlinear systems controlled by neural networks in the presence of disturbance and measurement noise. A robustly stable interval observer is designed to generate sound and precise lower and upper bounds for the neural network, nonlinear function, a… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.16132v1-abstract-full').style.display = 'inline'; document.getElementById('2403.16132v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2403.16132v1-abstract-full" style="display: none;"> There is an emerging trend in applying deep learning methods to control complex nonlinear systems. This paper considers enhancing the runtime safety of nonlinear systems controlled by neural networks in the presence of disturbance and measurement noise. A robustly stable interval observer is designed to generate sound and precise lower and upper bounds for the neural network, nonlinear function, and system state. The obtained interval is utilised to monitor the real-time system safety and detect faults in the system outputs or actuators. An adaptive cruise control vehicular system is simulated to demonstrate effectiveness of the proposed design. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2403.16132v1-abstract-full').style.display = 'none'; document.getElementById('2403.16132v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 24 March, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">Accepted to SAFEPROCESS 2024</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2312.07934">arXiv:2312.07934</a> <span> [<a href="https://arxiv.org/pdf/2312.07934">pdf</a>, <a href="https://arxiv.org/format/2312.07934">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> Toward Real World Stereo Image Super-Resolution via Hybrid Degradation Model and Discriminator for Implied Stereo Image Information </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zhou%2C+Y">Yuanbo Zhou</a>, <a href="/search/eess?searchtype=author&query=Xue%2C+Y">Yuyang Xue</a>, <a href="/search/eess?searchtype=author&query=Bi%2C+J">Jiang Bi</a>, <a href="/search/eess?searchtype=author&query=He%2C+W">Wenlin He</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+X">Xinlin Zhang</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+J">Jiajun Zhang</a>, <a href="/search/eess?searchtype=author&query=Deng%2C+W">Wei Deng</a>, <a href="/search/eess?searchtype=author&query=Nie%2C+R">Ruofeng Nie</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Junlin Lan</a>, <a href="/search/eess?searchtype=author&query=Gao%2C+Q">Qinquan Gao</a>, <a href="/search/eess?searchtype=author&query=Tong%2C+T">Tong Tong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2312.07934v1-abstract-short" style="display: inline;"> Real-world stereo image super-resolution has a significant influence on enhancing the performance of computer vision systems. Although existing methods for single-image super-resolution can be applied to improve stereo images, these methods often introduce notable modifications to the inherent disparity, resulting in a loss in the consistency of disparity between the original and the enhanced ster… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.07934v1-abstract-full').style.display = 'inline'; document.getElementById('2312.07934v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2312.07934v1-abstract-full" style="display: none;"> Real-world stereo image super-resolution has a significant influence on enhancing the performance of computer vision systems. Although existing methods for single-image super-resolution can be applied to improve stereo images, these methods often introduce notable modifications to the inherent disparity, resulting in a loss in the consistency of disparity between the original and the enhanced stereo images. To overcome this limitation, this paper proposes a novel approach that integrates a implicit stereo information discriminator and a hybrid degradation model. This combination ensures effective enhancement while preserving disparity consistency. The proposed method bridges the gap between the complex degradations in real-world stereo domain and the simpler degradations in real-world single-image super-resolution domain. Our results demonstrate impressive performance on synthetic and real datasets, enhancing visual perception while maintaining disparity consistency. The complete code is available at the following \href{https://github.com/fzuzyb/SCGLANet}{link}. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2312.07934v1-abstract-full').style.display = 'none'; document.getElementById('2312.07934v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2311.10349">arXiv:2311.10349</a> <span> [<a href="https://arxiv.org/pdf/2311.10349">pdf</a>, <a href="https://arxiv.org/format/2311.10349">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> </div> <p class="title is-5 mathjax"> Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Wang%2C+T">Tao Wang</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+Y">Yuanbin Chen</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+X">Xinlin Zhang</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+Y">Yuanbo Zhou</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Junlin Lan</a>, <a href="/search/eess?searchtype=author&query=Bai%2C+B">Bizhe Bai</a>, <a href="/search/eess?searchtype=author&query=Tan%2C+T">Tao Tan</a>, <a href="/search/eess?searchtype=author&query=Du%2C+M">Min Du</a>, <a href="/search/eess?searchtype=author&query=Gao%2C+Q">Qinquan Gao</a>, <a href="/search/eess?searchtype=author&query=Tong%2C+T">Tong Tong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2311.10349v1-abstract-short" style="display: inline;"> Supervised learning algorithms based on Convolutional Neural Networks have become the benchmark for medical image segmentation tasks, but their effectiveness heavily relies on a large amount of labeled data. However, annotating medical image datasets is a laborious and time-consuming process. Inspired by semi-supervised algorithms that use both labeled and unlabeled data for training, we propose t… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.10349v1-abstract-full').style.display = 'inline'; document.getElementById('2311.10349v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2311.10349v1-abstract-full" style="display: none;"> Supervised learning algorithms based on Convolutional Neural Networks have become the benchmark for medical image segmentation tasks, but their effectiveness heavily relies on a large amount of labeled data. However, annotating medical image datasets is a laborious and time-consuming process. Inspired by semi-supervised algorithms that use both labeled and unlabeled data for training, we propose the PLGDF framework, which builds upon the mean teacher network for segmenting medical images with less annotation. We propose a novel pseudo-label utilization scheme, which combines labeled and unlabeled data to augment the dataset effectively. Additionally, we enforce the consistency between different scales in the decoder module of the segmentation network and propose a loss function suitable for evaluating the consistency. Moreover, we incorporate a sharpening operation on the predicted results, further enhancing the accuracy of the segmentation. Extensive experiments on three publicly available datasets demonstrate that the PLGDF framework can largely improve performance by incorporating the unlabeled data. Meanwhile, our framework yields superior performance compared to six state-of-the-art semi-supervised learning methods. The codes of this study are available at https://github.com/ortonwang/PLGDF. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.10349v1-abstract-full').style.display = 'none'; document.getElementById('2311.10349v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2308.10009">arXiv:2308.10009</a> <span> [<a href="https://arxiv.org/pdf/2308.10009">pdf</a>, <a href="https://arxiv.org/format/2308.10009">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Realizing In-Memory Baseband Processing for Ultra-Fast and Energy-Efficient 6G </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zeng%2C+Q">Qunsong Zeng</a>, <a href="/search/eess?searchtype=author&query=Liu%2C+J">Jiawei Liu</a>, <a href="/search/eess?searchtype=author&query=Jiang%2C+M">Mingrui Jiang</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jun Lan</a>, <a href="/search/eess?searchtype=author&query=Gong%2C+Y">Yi Gong</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+Z">Zhongrui Wang</a>, <a href="/search/eess?searchtype=author&query=Li%2C+Y">Yida Li</a>, <a href="/search/eess?searchtype=author&query=Li%2C+C">Can Li</a>, <a href="/search/eess?searchtype=author&query=Ignowski%2C+J">Jim Ignowski</a>, <a href="/search/eess?searchtype=author&query=Huang%2C+K">Kaibin Huang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2308.10009v1-abstract-short" style="display: inline;"> To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neumann bottleneck. To address these challenges, in-… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.10009v1-abstract-full').style.display = 'inline'; document.getElementById('2308.10009v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2308.10009v1-abstract-full" style="display: none;"> To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neumann bottleneck. To address these challenges, in-memory computing-based baseband processors using resistive random-access memory (RRAM) present an attractive solution. In this paper, we propose and demonstrate RRAM-implemented in-memory baseband processing for the widely adopted multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) air interface. Its key feature is to execute the key operations, including discrete Fourier transform (DFT) and MIMO detection using linear minimum mean square error (L-MMSE) and zero forcing (ZF), in one-step. In addition, RRAM-based channel estimation module is proposed and discussed. By prototyping and simulations, we demonstrate the feasibility of RRAM-based full-fledged communication system in hardware, and reveal it can outperform state-of-the-art baseband processors with a gain of 91.2$\times$ in latency and 671$\times$ in energy efficiency by large-scale simulations. Our results pave a potential pathway for RRAM-based in-memory computing to be implemented in the era of the sixth generation (6G) mobile communications. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2308.10009v1-abstract-full').style.display = 'none'; document.getElementById('2308.10009v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 19 August, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">arXiv admin note: text overlap with arXiv:2205.03561</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.13643">arXiv:2307.13643</a> <span> [<a href="https://arxiv.org/pdf/2307.13643">pdf</a>, <a href="https://arxiv.org/format/2307.13643">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Sound">cs.SD</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Audio and Speech Processing">eess.AS</span> </div> </div> <p class="title is-5 mathjax"> Backdoor Attacks against Voice Recognition Systems: A Survey </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Yan%2C+B">Baochen Yan</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jiahe Lan</a>, <a href="/search/eess?searchtype=author&query=Yan%2C+Z">Zheng Yan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2307.13643v1-abstract-short" style="display: inline;"> Voice Recognition Systems (VRSs) employ deep learning for speech recognition and speaker recognition. They have been widely deployed in various real-world applications, from intelligent voice assistance to telephony surveillance and biometric authentication. However, prior research has revealed the vulnerability of VRSs to backdoor attacks, which pose a significant threat to the security and priva… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.13643v1-abstract-full').style.display = 'inline'; document.getElementById('2307.13643v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.13643v1-abstract-full" style="display: none;"> Voice Recognition Systems (VRSs) employ deep learning for speech recognition and speaker recognition. They have been widely deployed in various real-world applications, from intelligent voice assistance to telephony surveillance and biometric authentication. However, prior research has revealed the vulnerability of VRSs to backdoor attacks, which pose a significant threat to the security and privacy of VRSs. Unfortunately, existing literature lacks a thorough review on this topic. This paper fills this research gap by conducting a comprehensive survey on backdoor attacks against VRSs. We first present an overview of VRSs and backdoor attacks, elucidating their basic knowledge. Then we propose a set of evaluation criteria to assess the performance of backdoor attack methods. Next, we present a comprehensive taxonomy of backdoor attacks against VRSs from different perspectives and analyze the characteristic of different categories. After that, we comprehensively review existing attack methods and analyze their pros and cons based on the proposed criteria. Furthermore, we review classic backdoor defense methods and generic audio defense techniques. Then we discuss the feasibility of deploying them on VRSs. Finally, we figure out several open issues and further suggest future research directions to motivate the research of VRSs security. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.13643v1-abstract-full').style.display = 'none'; document.getElementById('2307.13643v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">33 pages, 7 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.13237">arXiv:2307.13237</a> <span> [<a href="https://arxiv.org/pdf/2307.13237">pdf</a>, <a href="https://arxiv.org/ps/2307.13237">ps</a>, <a href="https://arxiv.org/format/2307.13237">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1109/LWC.2023.3331489">10.1109/LWC.2023.3331489 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Rank Optimization for MIMO Channel with RIS: Simulation and Measurement </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Meng%2C+S">Shengguo Meng</a>, <a href="/search/eess?searchtype=author&query=Tang%2C+W">Wankai Tang</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+W">Weicong Chen</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jifeng Lan</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+Q+Y">Qun Yan Zhou</a>, <a href="/search/eess?searchtype=author&query=Han%2C+Y">Yu Han</a>, <a href="/search/eess?searchtype=author&query=Li%2C+X">Xiao Li</a>, <a href="/search/eess?searchtype=author&query=Jin%2C+S">Shi Jin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2307.13237v2-abstract-short" style="display: inline;"> Reconfigurable intelligent surface (RIS) is a promising technology that can reshape the electromagnetic environment in wireless networks, offering various possibilities for enhancing wireless channels. Motivated by this, we investigate the channel optimization for multiple-input multiple-output (MIMO) systems assisted by RIS. In this paper, an efficient RIS optimization method is proposed to enhan… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.13237v2-abstract-full').style.display = 'inline'; document.getElementById('2307.13237v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.13237v2-abstract-full" style="display: none;"> Reconfigurable intelligent surface (RIS) is a promising technology that can reshape the electromagnetic environment in wireless networks, offering various possibilities for enhancing wireless channels. Motivated by this, we investigate the channel optimization for multiple-input multiple-output (MIMO) systems assisted by RIS. In this paper, an efficient RIS optimization method is proposed to enhance the effective rank of the MIMO channel for achievable rate improvement. Numerical results are presented to verify the effectiveness of RIS in improving MIMO channels. Additionally, we construct a 2$\times$2 RIS-assisted MIMO prototype to perform experimental measurements and validate the performance of our proposed algorithm. The results reveal a significant increase in effective rank and achievable rate for the RIS-assisted MIMO channel compared to the MIMO channel without RIS. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.13237v2-abstract-full').style.display = 'none'; document.getElementById('2307.13237v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 December, 2023; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 25 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">This work has been accepted by IEEE WCL</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.11505">arXiv:2307.11505</a> <span> [<a href="https://arxiv.org/pdf/2307.11505">pdf</a>, <a href="https://arxiv.org/ps/2307.11505">ps</a>, <a href="https://arxiv.org/format/2307.11505">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Optimization and Control">math.OC</span> </div> </div> <p class="title is-5 mathjax"> Data-Driven Cooperative Adaptive Cruise Control for Unknown Nonlinear Vehicle Platoons </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2307.11505v1-abstract-short" style="display: inline;"> This paper studies cooperative adaptive cruise control (CACC) for vehicle platoons with consideration of the unknown nonlinear vehicle dynamics that are normally ignored in the literature. A unified data-driven CACC design is proposed for platoons of pure automated vehicles (AVs) or of mixed AVs and human-driven vehicles (HVs). The CACC leverages online-collected sufficient data samples of vehicle… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.11505v1-abstract-full').style.display = 'inline'; document.getElementById('2307.11505v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.11505v1-abstract-full" style="display: none;"> This paper studies cooperative adaptive cruise control (CACC) for vehicle platoons with consideration of the unknown nonlinear vehicle dynamics that are normally ignored in the literature. A unified data-driven CACC design is proposed for platoons of pure automated vehicles (AVs) or of mixed AVs and human-driven vehicles (HVs). The CACC leverages online-collected sufficient data samples of vehicle accelerations, spacing and relative velocities. The data-driven control design is formulated as a semidefinite program (SDP) that can be solved efficiently using off-the-shelf solvers. The efficacy and advantage of the proposed CACC are demonstrated through a comparison with the classic adaptive cruise control (ACC) method on a platoon of pure AVs and a mixed platoon under a representative aggressive driving profile. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.11505v1-abstract-full').style.display = 'none'; document.getElementById('2307.11505v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">6 pages, 5 figures; This paper is under submission</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2307.11476">arXiv:2307.11476</a> <span> [<a href="https://arxiv.org/pdf/2307.11476">pdf</a>, <a href="https://arxiv.org/format/2307.11476">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Optimization and Control">math.OC</span> </div> </div> <p class="title is-5 mathjax"> Data-driven dual-loop control for platooning mixed human-driven and automated vehicles </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jianglin Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2307.11476v1-abstract-short" style="display: inline;"> This paper considers controlling automated vehicles (AVs) to form a platoon with human-driven vehicles (HVs) under consideration of unknown HV model parameters and propulsion time constants. The proposed design is a data-driven dual-loop control strategy for the ego AVs, where the inner loop controller ensures platoon stability and the outer loop controller keeps a safe inter-vehicular spacing und… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.11476v1-abstract-full').style.display = 'inline'; document.getElementById('2307.11476v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2307.11476v1-abstract-full" style="display: none;"> This paper considers controlling automated vehicles (AVs) to form a platoon with human-driven vehicles (HVs) under consideration of unknown HV model parameters and propulsion time constants. The proposed design is a data-driven dual-loop control strategy for the ego AVs, where the inner loop controller ensures platoon stability and the outer loop controller keeps a safe inter-vehicular spacing under control input limits. The inner loop controller is a constant-gain state feedback controller solved from a semidefinite program (SDP) using the online collected data of platooning errors. The outer loop is a model predictive control (MPC) that embeds a data-driven internal model to predict the future platooning error evolution. The proposed design is evaluated on a mixed platoon with a representative aggressive reference velocity profile, the SFTP-US06 Drive Cycle. The results confirm efficacy of the design and its advantages over the existing single loop data-driven MPC in terms of platoon stability and computational cost. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2307.11476v1-abstract-full').style.display = 'none'; document.getElementById('2307.11476v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 July, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages, 6 figures. This paper has been accepted by IET Intelligent Transport Systems</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2306.16918">arXiv:2306.16918</a> <span> [<a href="https://arxiv.org/pdf/2306.16918">pdf</a>, <a href="https://arxiv.org/format/2306.16918">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Image and Video Processing">eess.IV</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computer Vision and Pattern Recognition">cs.CV</span> </div> </div> <p class="title is-5 mathjax"> PCDAL: A Perturbation Consistency-Driven Active Learning Approach for Medical Image Segmentation and Classification </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Wang%2C+T">Tao Wang</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+X">Xinlin Zhang</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+Y">Yuanbo Zhou</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Junlin Lan</a>, <a href="/search/eess?searchtype=author&query=Tan%2C+T">Tao Tan</a>, <a href="/search/eess?searchtype=author&query=Du%2C+M">Min Du</a>, <a href="/search/eess?searchtype=author&query=Gao%2C+Q">Qinquan Gao</a>, <a href="/search/eess?searchtype=author&query=Tong%2C+T">Tong Tong</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2306.16918v1-abstract-short" style="display: inline;"> In recent years, deep learning has become a breakthrough technique in assisting medical image diagnosis. Supervised learning using convolutional neural networks (CNN) provides state-of-the-art performance and has served as a benchmark for various medical image segmentation and classification. However, supervised learning deeply relies on large-scale annotated data, which is expensive, time-consumi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.16918v1-abstract-full').style.display = 'inline'; document.getElementById('2306.16918v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2306.16918v1-abstract-full" style="display: none;"> In recent years, deep learning has become a breakthrough technique in assisting medical image diagnosis. Supervised learning using convolutional neural networks (CNN) provides state-of-the-art performance and has served as a benchmark for various medical image segmentation and classification. However, supervised learning deeply relies on large-scale annotated data, which is expensive, time-consuming, and even impractical to acquire in medical imaging applications. Active Learning (AL) methods have been widely applied in natural image classification tasks to reduce annotation costs by selecting more valuable examples from the unlabeled data pool. However, their application in medical image segmentation tasks is limited, and there is currently no effective and universal AL-based method specifically designed for 3D medical image segmentation. To address this limitation, we propose an AL-based method that can be simultaneously applied to 2D medical image classification, segmentation, and 3D medical image segmentation tasks. We extensively validated our proposed active learning method on three publicly available and challenging medical image datasets, Kvasir Dataset, COVID-19 Infection Segmentation Dataset, and BraTS2019 Dataset. The experimental results demonstrate that our PCDAL can achieve significantly improved performance with fewer annotations in 2D classification and segmentation and 3D segmentation tasks. The codes of this study are available at https://github.com/ortonwang/PCDAL. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2306.16918v1-abstract-full').style.display = 'none'; document.getElementById('2306.16918v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 June, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> June 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2303.13046">arXiv:2303.13046</a> <span> [<a href="https://arxiv.org/pdf/2303.13046">pdf</a>, <a href="https://arxiv.org/format/2303.13046">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Information Theory">cs.IT</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Quantized Phase Alignment by Discrete Phase Shifts for Reconfigurable Intelligent Surface-Assisted Communication Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Sang%2C+J">Jian Sang</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jifeng Lan</a>, <a href="/search/eess?searchtype=author&query=Zhou%2C+M">Mingyong Zhou</a>, <a href="/search/eess?searchtype=author&query=Gao%2C+B">Boning Gao</a>, <a href="/search/eess?searchtype=author&query=Tang%2C+W">Wankai Tang</a>, <a href="/search/eess?searchtype=author&query=Li%2C+X">Xiao Li</a>, <a href="/search/eess?searchtype=author&query=Yi%2C+X">Xinping Yi</a>, <a href="/search/eess?searchtype=author&query=Jin%2C+S">Shi Jin</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2303.13046v1-abstract-short" style="display: inline;"> Reconfigurable intelligent surface (RIS) has aroused a surge of interest in recent years. In this paper, we investigate the joint phase alignment and phase quantization on discrete phase shift designs for RIS-assisted single-input single-output (SISO) system. Firstly, the phenomena of phase distribution in far field and near field are respectively unveiled, paving the way for discretization of pha… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.13046v1-abstract-full').style.display = 'inline'; document.getElementById('2303.13046v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2303.13046v1-abstract-full" style="display: none;"> Reconfigurable intelligent surface (RIS) has aroused a surge of interest in recent years. In this paper, we investigate the joint phase alignment and phase quantization on discrete phase shift designs for RIS-assisted single-input single-output (SISO) system. Firstly, the phenomena of phase distribution in far field and near field are respectively unveiled, paving the way for discretization of phase shift for RIS. Then, aiming at aligning phases, the phase distribution law and its underlying degree-of-freedom (DoF) are characterized, serving as the guideline of phase quantization strategies. Subsequently, two phase quantization methods, dynamic threshold phase quantization (DTPQ) and equal interval phase quantization (EIPQ), are proposed to strengthen the beamforming effect of RIS. DTPQ is capable of calculating the optimal discrete phase shifts with linear complexity in the number of unit cells on RIS, whilst EIPQ is a simplified method with a constant complexity yielding sub-optimal solution. Simulation results demonstrate that both methods achieve substantial improvements on power gain, stability, and robustness over traditional quantization methods. The path loss (PL) scaling law under discrete phase shift of RIS is unveiled for the first time, with the phase shifts designed by DTPQ due to its optimality. Additionally, the field trials conducted at 2.6 GHz and 35 GHz validate the favourable performance of the proposed methods in practical communication environment. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2303.13046v1-abstract-full').style.display = 'none'; document.getElementById('2303.13046v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 23 March, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2023. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2205.13685">arXiv:2205.13685</a> <span> [<a href="https://arxiv.org/pdf/2205.13685">pdf</a>, <a href="https://arxiv.org/format/2205.13685">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Cryptography and Security">cs.CR</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Sound">cs.SD</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Audio and Speech Processing">eess.AS</span> </div> </div> <p class="title is-5 mathjax"> Adversarial attacks and defenses in Speaker Recognition Systems: A survey </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jiahe Lan</a>, <a href="/search/eess?searchtype=author&query=Zhang%2C+R">Rui Zhang</a>, <a href="/search/eess?searchtype=author&query=Yan%2C+Z">Zheng Yan</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+J">Jie Wang</a>, <a href="/search/eess?searchtype=author&query=Chen%2C+Y">Yu Chen</a>, <a href="/search/eess?searchtype=author&query=Hou%2C+R">Ronghui Hou</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2205.13685v1-abstract-short" style="display: inline;"> Speaker recognition has become very popular in many application scenarios, such as smart homes and smart assistants, due to ease of use for remote control and economic-friendly features. The rapid development of SRSs is inseparable from the advancement of machine learning, especially neural networks. However, previous work has shown that machine learning models are vulnerable to adversarial attack… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2205.13685v1-abstract-full').style.display = 'inline'; document.getElementById('2205.13685v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2205.13685v1-abstract-full" style="display: none;"> Speaker recognition has become very popular in many application scenarios, such as smart homes and smart assistants, due to ease of use for remote control and economic-friendly features. The rapid development of SRSs is inseparable from the advancement of machine learning, especially neural networks. However, previous work has shown that machine learning models are vulnerable to adversarial attacks in the image domain, which inspired researchers to explore adversarial attacks and defenses in Speaker Recognition Systems (SRS). Unfortunately, existing literature lacks a thorough review of this topic. In this paper, we fill this gap by performing a comprehensive survey on adversarial attacks and defenses in SRSs. We first introduce the basics of SRSs and concepts related to adversarial attacks. Then, we propose two sets of criteria to evaluate the performance of attack methods and defense methods in SRSs, respectively. After that, we provide taxonomies of existing attack methods and defense methods, and further review them by employing our proposed criteria. Finally, based on our review, we find some open issues and further specify a number of future directions to motivate the research of SRSs security. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2205.13685v1-abstract-full').style.display = 'none'; document.getElementById('2205.13685v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 May, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">38pages, 2 figures, 2 tables. Journal of Systems Architecture,2022</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">ACM Class:</span> A.1 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2205.03561">arXiv:2205.03561</a> <span> [<a href="https://arxiv.org/pdf/2205.03561">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Realizing Ultra-Fast and Energy-Efficient Baseband Processing Using Analogue Resistive Switching Memory </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Zeng%2C+Q">Qunsong Zeng</a>, <a href="/search/eess?searchtype=author&query=Liu%2C+J">Jiawei Liu</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jun Lan</a>, <a href="/search/eess?searchtype=author&query=Gong%2C+Y">Yi Gong</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+Z">Zhongrui Wang</a>, <a href="/search/eess?searchtype=author&query=Li%2C+Y">Yida Li</a>, <a href="/search/eess?searchtype=author&query=Huang%2C+K">Kaibin Huang</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2205.03561v1-abstract-short" style="display: inline;"> To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neumann bottleneck. To address these challeng… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2205.03561v1-abstract-full').style.display = 'inline'; document.getElementById('2205.03561v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2205.03561v1-abstract-full" style="display: none;"> To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neumann bottleneck. To address these challenges, in-memory computing-based baseband processors using resistive random-access memory (RRAM) present an attractive solution. In this paper, we propose and demonstrate RRAM-based in-memory baseband processing for the widely adopted multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) air interface. Its key feature is to execute the key operations, including discrete Fourier transform (DFT) and MIMO detection using linear minimum mean square error (L-MMSE) and zero forcing (ZF), in one-step. In addition, RRAM-based channel estimation as well as mapper/demapper modules are proposed. By prototyping and simulations, we demonstrate that the RRAM-based full-fledged communication system can significantly outperform its CMOS-based counterpart in terms of speed and energy efficiency by $10^3$ and $10^6$ times, respectively. The results pave a potential pathway for RRAM-based in-memory computing to be implemented in the era of the sixth generation (6G) mobile communications. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2205.03561v1-abstract-full').style.display = 'none'; document.getElementById('2205.03561v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 May, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2022. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2012.15164">arXiv:2012.15164</a> <span> [<a href="https://arxiv.org/pdf/2012.15164">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Robotics">cs.RO</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Systems and Control">eess.SY</span> </div> </div> <p class="title is-5 mathjax"> Analysis of Truck Driver Behavior to Design Different Lane Change Styles in Automated Driving </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Wang%2C+Z">Zheng Wang</a>, <a href="/search/eess?searchtype=author&query=Guan%2C+M">Muhua Guan</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jin Lan</a>, <a href="/search/eess?searchtype=author&query=Yang%2C+B">Bo Yang</a>, <a href="/search/eess?searchtype=author&query=Kaizuka%2C+T">Tsutomu Kaizuka</a>, <a href="/search/eess?searchtype=author&query=Taki%2C+J">Junichi Taki</a>, <a href="/search/eess?searchtype=author&query=Nakano%2C+K">Kimihiko Nakano</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2012.15164v1-abstract-short" style="display: inline;"> Lane change is a very demanding driving task and number of traffic accidents are induced by mistaken maneuvers. An automated lane change system has the potential to reduce driver workload and to improve driving safety. One challenge is how to improve driver acceptance on the automated system. From the viewpoint of human factors, an automated system with different styles would improve user acceptan… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2012.15164v1-abstract-full').style.display = 'inline'; document.getElementById('2012.15164v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2012.15164v1-abstract-full" style="display: none;"> Lane change is a very demanding driving task and number of traffic accidents are induced by mistaken maneuvers. An automated lane change system has the potential to reduce driver workload and to improve driving safety. One challenge is how to improve driver acceptance on the automated system. From the viewpoint of human factors, an automated system with different styles would improve user acceptance as the drivers can adapt the style to different driving situations. This paper proposes a method to design different lane change styles in automated driving by analysis and modeling of truck driver behavior. A truck driving simulator experiment with 12 participants was conducted to identify the driver model parameters and three lane change styles were classified as the aggressive, medium, and conservative ones. The proposed automated lane change system was evaluated by another truck driving simulator experiment with the same 12 participants. Moreover, the effect of different driving styles on driver experience and acceptance was evaluated. The evaluation results demonstrate that the different lane change styles could be distinguished by the drivers; meanwhile, the three styles were overall evaluated as acceptable on safety issues and reliable by the human drivers. This study provides insight into designing the automated driving system with different driving styles and the findings can be applied to commercial automated trucks. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2012.15164v1-abstract-full').style.display = 'none'; document.getElementById('2012.15164v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 December, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2020. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1912.05531">arXiv:1912.05531</a> <span> [<a href="https://arxiv.org/pdf/1912.05531">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Geophysics">physics.geo-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Signal Processing">eess.SP</span> </div> </div> <p class="title is-5 mathjax"> Deep learning for magnitude prediction in earthquake early warning </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/eess?searchtype=author&query=Wang%2C+Y">Yanwei Wang</a>, <a href="/search/eess?searchtype=author&query=Wang%2C+Z">Zifa Wang</a>, <a href="/search/eess?searchtype=author&query=Cao%2C+Z">Zhenzhong Cao</a>, <a href="/search/eess?searchtype=author&query=Lan%2C+J">Jingyan Lan</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1912.05531v2-abstract-short" style="display: inline;"> Fast and accurate magnitude prediction is the key to the success of earthquake early warning. We have proposed a new approach based on deep learning for P-wave magnitude prediction (EEWNet), which takes time series data as input instead of feature parameters. The architecture of EEWNet is adaptively adjusted according to the length of the input, thus eliminates the need of complicated tuning of hy… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1912.05531v2-abstract-full').style.display = 'inline'; document.getElementById('1912.05531v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1912.05531v2-abstract-full" style="display: none;"> Fast and accurate magnitude prediction is the key to the success of earthquake early warning. We have proposed a new approach based on deep learning for P-wave magnitude prediction (EEWNet), which takes time series data as input instead of feature parameters. The architecture of EEWNet is adaptively adjusted according to the length of the input, thus eliminates the need of complicated tuning of hyperparameters for deep learning. Only the unfiltered accelerograms of vertical components are used. EEWNet is trained on a moderate number of data set (10,000s of records), but it achieves excellent results in magnitude prediction compared with approaches using parameters 蟿log, 蟿c and Pd. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1912.05531v2-abstract-full').style.display = 'none'; document.getElementById('1912.05531v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 July, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 2 December, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2019. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">6 pages, 4 figures</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" 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