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time domain estimation</title> <meta name="description" content="Search results for: continuous time domain estimation"> <meta name="keywords" content="continuous time domain estimation"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> 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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="continuous time domain estimation"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 22154</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: continuous time domain estimation</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22154</span> Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Cheng%20Zhang">Cheng Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=James%20Marco"> James Marco</a>, <a href="https://publications.waset.org/abstracts/search?q=Walid%20Allafi"> Walid Allafi</a>, <a href="https://publications.waset.org/abstracts/search?q=Truong%20Q.%20Dinh"> Truong Q. Dinh</a>, <a href="https://publications.waset.org/abstracts/search?q=W.%20D.%20Widanage"> W. D. Widanage</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electric%20circuit%20model" title="electric circuit model">electric circuit model</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous%20time%20domain%20estimation" title=" continuous time domain estimation"> continuous time domain estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20integral%20filter%20method" title=" linear integral filter method"> linear integral filter method</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20and%20SOC%20estimation" title=" parameter and SOC estimation"> parameter and SOC estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=recursive%20least%20square" title=" recursive least square"> recursive least square</a> </p> <a href="https://publications.waset.org/abstracts/67718/online-battery-equivalent-circuit-model-estimation-on-continuous-time-domain-using-linear-integral-filter-method" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67718.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">383</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22153</span> Single Carrier Frequency Domain Equalization Design to Cope with Narrow Band Jammer</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=So-Young%20Ju">So-Young Ju</a>, <a href="https://publications.waset.org/abstracts/search?q=Sung-Mi%20Jo"> Sung-Mi Jo</a>, <a href="https://publications.waset.org/abstracts/search?q=Eui-Rim%20Jeong"> Eui-Rim Jeong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, based on the conventional single carrier frequency domain equalization (SC-FDE) structure, we propose a new SC-FDE structure to cope with narrowband jammer. In the conventional SC-FDE structure, channel estimation is performed in the time domain. When a narrowband jammer exists, time-domain channel estimation is very difficult due to high power jamming interference, which degrades receiver performance. To relieve from this problem, a new SC-FDE frame is proposed to enable channel estimation under narrow band jamming environments. In this paper, we proposed a modified SC-FDE structure that can perform channel estimation in the frequency domain and verified the performance via computer simulation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title="channel estimation">channel estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=jammer" title=" jammer"> jammer</a>, <a href="https://publications.waset.org/abstracts/search?q=pilot" title=" pilot"> pilot</a>, <a href="https://publications.waset.org/abstracts/search?q=SC-FDE" title=" SC-FDE"> SC-FDE</a> </p> <a href="https://publications.waset.org/abstracts/80488/single-carrier-frequency-domain-equalization-design-to-cope-with-narrow-band-jammer" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80488.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">475</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22152</span> Channel Estimation for LTE Downlink</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rashi%20Jain">Rashi Jain</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=LTE" title="LTE">LTE</a>, <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title=" channel estimation"> channel estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=OFDM" title=" OFDM"> OFDM</a>, <a href="https://publications.waset.org/abstracts/search?q=RLS" title=" RLS"> RLS</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a>, <a href="https://publications.waset.org/abstracts/search?q=threshold" title=" threshold"> threshold</a> </p> <a href="https://publications.waset.org/abstracts/9169/channel-estimation-for-lte-downlink" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9169.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">356</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22151</span> Frequency Selective Filters for Estimating the Equivalent Circuit Parameters of Li-Ion Battery</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Arpita%20Mondal">Arpita Mondal</a>, <a href="https://publications.waset.org/abstracts/search?q=Aurobinda%20Routray"> Aurobinda Routray</a>, <a href="https://publications.waset.org/abstracts/search?q=Sreeraj%20Puravankara"> Sreeraj Puravankara</a>, <a href="https://publications.waset.org/abstracts/search?q=Rajashree%20Biswas"> Rajashree Biswas</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The most difficult part of designing a battery management system (BMS) is battery modeling. A good battery model can capture the dynamics which helps in energy management, by accurate model-based state estimation algorithms. So far the most suitable and fruitful model is the equivalent circuit model (ECM). However, in real-time applications, the model parameters are time-varying, changes with current, temperature, state of charge (SOC), and aging of the battery and this make a great impact on the performance of the model. Therefore, to increase the equivalent circuit model performance, the parameter estimation has been carried out in the frequency domain. The battery is a very complex system, which is associated with various chemical reactions and heat generation. Therefore, it’s very difficult to select the optimal model structure. As we know, if the model order is increased, the model accuracy will be improved automatically. However, the higher order model will face the tendency of over-parameterization and unfavorable prediction capability, while the model complexity will increase enormously. In the time domain, it becomes difficult to solve higher order differential equations as the model order increases. This problem can be resolved by frequency domain analysis, where the overall computational problems due to ill-conditioning reduce. In the frequency domain, several dominating frequencies can be found in the input as well as output data. The selective frequency domain estimation has been carried out, first by estimating the frequencies of the input and output by subspace decomposition, then by choosing the specific bands from the most dominating to the least, while carrying out the least-square, recursive least square and Kalman Filter based parameter estimation. In this paper, a second order battery model consisting of three resistors, two capacitors, and one SOC controlled voltage source has been chosen. For model identification and validation hybrid pulse power characterization (HPPC) tests have been carried out on a 2.6 Ah LiFePO₄ battery. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=equivalent%20circuit%20model" title="equivalent circuit model">equivalent circuit model</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20estimation" title=" frequency estimation"> frequency estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title=" parameter estimation"> parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=subspace%20decomposition" title=" subspace decomposition"> subspace decomposition</a> </p> <a href="https://publications.waset.org/abstracts/108720/frequency-selective-filters-for-estimating-the-equivalent-circuit-parameters-of-li-ion-battery" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108720.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22150</span> Continuous Differential Evolution Based Parameter Estimation Framework for Signal Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ammara%20Mehmood">Ammara Mehmood</a>, <a href="https://publications.waset.org/abstracts/search?q=Aneela%20Zameer"> Aneela Zameer</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Asif%20Zahoor%20Raja"> Muhammad Asif Zahoor Raja</a>, <a href="https://publications.waset.org/abstracts/search?q=Muhammad%20Faisal%20Fateh"> Muhammad Faisal Fateh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, the strength of bio-inspired computational intelligence based technique is exploited for parameter estimation for the periodic signals using Continuous Differential Evolution (CDE) by deﬁning an error function in the mean square sense. Multidimensional and nonlinear nature of the problem emerging in sinusoidal signal models along with noise makes it a challenging optimization task, which is dealt with robustness and effectiveness of CDE to ensure convergence and avoid trapping in local minima. In the proposed scheme of Continuous Differential Evolution based Signal Parameter Estimation (CDESPE), unknown adjustable weights of the signal system identification model are optimized utilizing CDE algorithm. The performance of CDESPE model is validated through statistics based various performance indices on a sufficiently large number of runs in terms of estimation error, mean squared error and Thiel’s inequality coefﬁcient. Efficacy of CDESPE is examined by comparison with the actual parameters of the system, Genetic Algorithm based outcomes and from various deterministic approaches at different signal-to-noise ratio (SNR) levels. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parameter%20estimation" title="parameter estimation">parameter estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=bio-inspired%20computing" title=" bio-inspired computing"> bio-inspired computing</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous%20differential%20evolution%20%28CDE%29" title=" continuous differential evolution (CDE)"> continuous differential evolution (CDE)</a>, <a href="https://publications.waset.org/abstracts/search?q=periodic%20signals" title=" periodic signals"> periodic signals</a> </p> <a href="https://publications.waset.org/abstracts/72735/continuous-differential-evolution-based-parameter-estimation-framework-for-signal-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72735.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">302</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22149</span> Continuous-Time and Discrete-Time Singular Value Decomposition of an Impulse Response Function</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rogelio%20Luck">Rogelio Luck</a>, <a href="https://publications.waset.org/abstracts/search?q=Yucheng%20Liu"> Yucheng Liu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes the continuous-time singular value decomposition (SVD) for the impulse response function, a special kind of Green’s functions e⁻⁽ᵗ⁻ ᵀ⁾, in order to find a set of singular functions and singular values so that the convolutions of such function with the set of singular functions on a specified domain are the solutions to the inhomogeneous differential equations for those singular functions. A numerical example was illustrated to verify the proposed method. Besides the continuous-time SVD, a discrete-time SVD is also presented for the impulse response function, which is modeled using a Toeplitz matrix in the discrete system. The proposed method has broad applications in signal processing, dynamic system analysis, acoustic analysis, thermal analysis, as well as macroeconomic modeling. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=singular%20value%20decomposition" title="singular value decomposition">singular value decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=impulse%20response%20function" title=" impulse response function"> impulse response function</a>, <a href="https://publications.waset.org/abstracts/search?q=Green%E2%80%99s%20function" title=" Green’s function "> Green’s function </a>, <a href="https://publications.waset.org/abstracts/search?q=Toeplitz%20matrix" title=" Toeplitz matrix "> Toeplitz matrix </a>, <a href="https://publications.waset.org/abstracts/search?q=Hankel%20matrix" title=" Hankel matrix"> Hankel matrix</a> </p> <a href="https://publications.waset.org/abstracts/127083/continuous-time-and-discrete-time-singular-value-decomposition-of-an-impulse-response-function" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/127083.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">156</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22148</span> Comparison of Frequency-Domain Contention Schemes in Wireless LANs </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Li%20Feng">Li Feng</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In IEEE 802.11 networks, it is well known that the traditional time-domain contention often leads to low channel utilization. The first frequency-domain contention scheme, the time to frequency (T2F), has recently been proposed to improve the channel utilization and has attracted a great deal of attention. In this paper, we survey the latest research progress on the weighed frequency-domain contention. We present the basic ideas, work principles of these related schemes and point out their differences. This paper is very useful for further study on frequency-domain contention. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=802.11" title="802.11">802.11</a>, <a href="https://publications.waset.org/abstracts/search?q=wireless%20LANs" title=" wireless LANs"> wireless LANs</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency-domain%20contention" title=" frequency-domain contention"> frequency-domain contention</a>, <a href="https://publications.waset.org/abstracts/search?q=T2F" title=" T2F"> T2F</a> </p> <a href="https://publications.waset.org/abstracts/42959/comparison-of-frequency-domain-contention-schemes-in-wireless-lans" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42959.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">459</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22147</span> Observer-Based Control Design for Double Integrators Systems with Long Sampling Periods and Actuator Uncertainty</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tomas%20Menard">Tomas Menard</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamical%20system" title="dynamical system">dynamical system</a>, <a href="https://publications.waset.org/abstracts/search?q=control%20law%20design" title=" control law design"> control law design</a>, <a href="https://publications.waset.org/abstracts/search?q=sampled%20output" title=" sampled output"> sampled output</a>, <a href="https://publications.waset.org/abstracts/search?q=observer%20design" title=" observer design"> observer design</a> </p> <a href="https://publications.waset.org/abstracts/87913/observer-based-control-design-for-double-integrators-systems-with-long-sampling-periods-and-actuator-uncertainty" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87913.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">187</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22146</span> Overhead Reduction by Channel Estimation Using Linear Interpolation for Single Carrier Frequency Domain Equalization Transmission</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Min-Su%20Song">Min-Su Song</a>, <a href="https://publications.waset.org/abstracts/search?q=Haeng-Bok%20Kil"> Haeng-Bok Kil</a>, <a href="https://publications.waset.org/abstracts/search?q=Eui-Rim%20Jeong"> Eui-Rim Jeong</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper proposes a new method to reduce the overhead by pilots for single carrier frequency domain equalization (SC-FDE) transmission. In the conventional SC-FDE transmission structure, the overhead by transmitting pilot is heavy because the pilot are transmitted at every SC-FDE block. The proposed SC-FDE structure has fewer pilots and many SC-FCE blocks are transmitted between pilots. The channel estimation and equalization is performed at the pilot period and the channels between pilots are estimated through linear interpolation. This reduces the pilot overhead by reducing the pilot transmission compared with the conventional structure, and enables reliable channel estimation and equalization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=channel%20estimation" title="channel estimation">channel estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20interpolation" title=" linear interpolation"> linear interpolation</a>, <a href="https://publications.waset.org/abstracts/search?q=pilot%20overhead" title=" pilot overhead"> pilot overhead</a>, <a href="https://publications.waset.org/abstracts/search?q=SC-FDE" title=" SC-FDE"> SC-FDE</a> </p> <a href="https://publications.waset.org/abstracts/80487/overhead-reduction-by-channel-estimation-using-linear-interpolation-for-single-carrier-frequency-domain-equalization-transmission" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80487.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">273</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22145</span> Estimation of the Pore Electrical Conductivity Using Dielectric Sensors</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fethi%20Bouksila">Fethi Bouksila</a>, <a href="https://publications.waset.org/abstracts/search?q=Magnus%20Persson"> Magnus Persson</a>, <a href="https://publications.waset.org/abstracts/search?q=Ronny%20%20Berndtsson"> Ronny Berndtsson</a>, <a href="https://publications.waset.org/abstracts/search?q=Akissa%20Bahri"> Akissa Bahri</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Under salinity conditions, we evaluate the performance of Hilhost (2000) model to predict pore electrical conductivity ECp from dielectric permittivity and bulk electrical conductivity (ECa) using Time and Frequency Domain Reflectometry sensors (TDR, FDR). Using FDR_WET sensor, RMSE of ECp was 4.15 dS m-1. By replacing the standard soil parameter (K0) in Hilhost model by K0-ECa relationship, the RMSE of ECp decreased to 0.68 dS m-1. WET sensor could give similar accuracy to estimate ECp than TDR if calibrated values of K0 were used instead of standard values in Hilhost model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hilhost%20model" title="hilhost model">hilhost model</a>, <a href="https://publications.waset.org/abstracts/search?q=soil%20salinity" title=" soil salinity"> soil salinity</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20domain%20reflectometry" title=" time domain reflectometry"> time domain reflectometry</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20domain%20reflectometry" title=" frequency domain reflectometry"> frequency domain reflectometry</a>, <a href="https://publications.waset.org/abstracts/search?q=dielectric%20methods" title=" dielectric methods"> dielectric methods</a> </p> <a href="https://publications.waset.org/abstracts/146047/estimation-of-the-pore-electrical-conductivity-using-dielectric-sensors" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/146047.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">135</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22144</span> Detection of Parkinsonian Freezing of Gait</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sang-Hoon%20Park">Sang-Hoon Park</a>, <a href="https://publications.waset.org/abstracts/search?q=Yeji%20Ho"> Yeji Ho</a>, <a href="https://publications.waset.org/abstracts/search?q=Gwang-Moon%20Eom"> Gwang-Moon Eom</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Fast and accurate detection of Freezing of Gait (FOG) is desirable for appropriate application of cueing which has been shown to ameliorate FOG. Utilization of frequency spectrum of leg acceleration to derive the freeze index requires much calculation and it would lead to delayed cueing. We hypothesized that FOG can be reasonably detected from the time domain amplitude of foot acceleration. A time instant was recognized as FOG if the mean amplitude of the acceleration in the time window surrounding the time instant was in the specific FOG range. Parameters required in the FOG detection was optimized by simulated annealing. The suggested time domain methods showed performances comparable to those of frequency domain methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=freezing%20of%20gait" title="freezing of gait">freezing of gait</a>, <a href="https://publications.waset.org/abstracts/search?q=detection" title=" detection"> detection</a>, <a href="https://publications.waset.org/abstracts/search?q=Parkinson%27s%20disease" title=" Parkinson's disease"> Parkinson's disease</a>, <a href="https://publications.waset.org/abstracts/search?q=time-domain%20method" title=" time-domain method"> time-domain method</a> </p> <a href="https://publications.waset.org/abstracts/4337/detection-of-parkinsonian-freezing-of-gait" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4337.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22143</span> Basic Calibration and Normalization Techniques for Time Domain Reflectometry Measurements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shagufta%20Tabassum">Shagufta Tabassum</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study of dielectric properties in a binary mixture of liquids is very useful to understand the liquid structure, molecular interaction, dynamics, and kinematics of the mixture. Time-domain reflectometry (TDR) is a powerful tool for studying the cooperation and molecular dynamics of the H-bonded system. In this paper, we discuss the basic calibration and normalization procedure for time-domain reflectometry measurements. Our approach is to explain the different types of error occur during TDR measurements and how these errors can be eliminated or minimized. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=time%20domain%20reflectometry%20measurement%20techinque" title="time domain reflectometry measurement techinque">time domain reflectometry measurement techinque</a>, <a href="https://publications.waset.org/abstracts/search?q=cable%20and%20connector%20loss" title=" cable and connector loss"> cable and connector loss</a>, <a href="https://publications.waset.org/abstracts/search?q=oscilloscope%20loss" title=" oscilloscope loss"> oscilloscope loss</a>, <a href="https://publications.waset.org/abstracts/search?q=and%20normalization%20technique" title=" and normalization technique"> and normalization technique</a> </p> <a href="https://publications.waset.org/abstracts/139922/basic-calibration-and-normalization-techniques-for-time-domain-reflectometry-measurements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/139922.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">206</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22142</span> Frequency Domain Decomposition, Stochastic Subspace Identification and Continuous Wavelet Transform for Operational Modal Analysis of Three Story Steel Frame</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ardalan%20Sabamehr">Ardalan Sabamehr</a>, <a href="https://publications.waset.org/abstracts/search?q=Ashutosh%20Bagchi"> Ashutosh Bagchi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Recently, Structural Health Monitoring (SHM) based on the vibration of structures has attracted the attention of researchers in different fields such as: civil, aeronautical and mechanical engineering. Operational Modal Analysis (OMA) have been developed to identify modal properties of infrastructure such as bridge, building and so on. Frequency Domain Decomposition (FDD), Stochastic Subspace Identification (SSI) and Continuous Wavelet Transform (CWT) are the three most common methods in output only modal identification. FDD, SSI, and CWT operate based on the frequency domain, time domain, and time-frequency plane respectively. So, FDD and SSI are not able to display time and frequency at the same time. By the way, FDD and SSI have some difficulties in a noisy environment and finding the closed modes. CWT technique which is currently developed works on time-frequency plane and a reasonable performance in such condition. The other advantage of wavelet transform rather than other current techniques is that it can be applied for the non-stationary signal as well. The aim of this paper is to compare three most common modal identification techniques to find modal properties (such as natural frequency, mode shape, and damping ratio) of three story steel frame which was built in Concordia University Lab by use of ambient vibration. The frame has made of Galvanized steel with 60 cm length, 27 cm width and 133 cm height with no brace along the long span and short space. Three uniaxial wired accelerations (MicroStarin with 100mv/g accuracy) have been attached to the middle of each floor and gateway receives the data and send to the PC by use of Node Commander Software. The real-time monitoring has been performed for 20 seconds with 512 Hz sampling rate. The test is repeated for 5 times in each direction by hand shaking and impact hammer. CWT is able to detect instantaneous frequency by used of ridge detection method. In this paper, partial derivative ridge detection technique has been applied to the local maxima of time-frequency plane to detect the instantaneous frequency. The extracted result from all three methods have been compared, and it demonstrated that CWT has the better performance in term of its accuracy in noisy environment. The modal parameters such as natural frequency, damping ratio and mode shapes are identified from all three methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ambient%20vibration" title="ambient vibration">ambient vibration</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20domain%20decomposition" title=" frequency domain decomposition"> frequency domain decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20subspace%20identification" title=" stochastic subspace identification"> stochastic subspace identification</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous%20wavelet%20transform" title=" continuous wavelet transform"> continuous wavelet transform</a> </p> <a href="https://publications.waset.org/abstracts/56951/frequency-domain-decomposition-stochastic-subspace-identification-and-continuous-wavelet-transform-for-operational-modal-analysis-of-three-story-steel-frame" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/56951.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">296</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22141</span> Random Access in IoT Using Naïve Bayes Classification</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alhusein%20Almahjoub">Alhusein Almahjoub</a>, <a href="https://publications.waset.org/abstracts/search?q=Dongyu%20Qiu"> Dongyu Qiu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=random%20access" title="random access">random access</a>, <a href="https://publications.waset.org/abstracts/search?q=LTE%2FLTE-A" title=" LTE/LTE-A"> LTE/LTE-A</a>, <a href="https://publications.waset.org/abstracts/search?q=5G" title=" 5G"> 5G</a>, <a href="https://publications.waset.org/abstracts/search?q=machine%20learning" title=" machine learning"> machine learning</a>, <a href="https://publications.waset.org/abstracts/search?q=Na%C3%AFve%20Bayes%20estimation" title=" Naïve Bayes estimation"> Naïve Bayes estimation</a> </p> <a href="https://publications.waset.org/abstracts/134730/random-access-in-iot-using-naive-bayes-classification" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/134730.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">145</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22140</span> Particle Size Distribution Estimation of a Mixture of Regular and Irregular Sized Particles Using Acoustic Emissions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ejay%20Nsugbe">Ejay Nsugbe</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrew%20Starr"> Andrew Starr</a>, <a href="https://publications.waset.org/abstracts/search?q=Ian%20Jennions"> Ian Jennions</a>, <a href="https://publications.waset.org/abstracts/search?q=Cristobal%20Ruiz-Carcel"> Cristobal Ruiz-Carcel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=acoustic%20emissions" title="acoustic emissions">acoustic emissions</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20sizing" title=" particle sizing"> particle sizing</a>, <a href="https://publications.waset.org/abstracts/search?q=process%20monitoring" title=" process monitoring"> process monitoring</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a> </p> <a href="https://publications.waset.org/abstracts/68042/particle-size-distribution-estimation-of-a-mixture-of-regular-and-irregular-sized-particles-using-acoustic-emissions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68042.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">352</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22139</span> Time Delay Estimation Using Signal Envelopes for Synchronisation of Recordings</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sergei%20Aleinik">Sergei Aleinik</a>, <a href="https://publications.waset.org/abstracts/search?q=Mikhail%20Stolbov"> Mikhail Stolbov</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this work, a method of time delay estimation for dual-channel acoustic signals (speech, music, etc.) recorded under reverberant conditions is investigated. Standard methods based on cross-correlation of the signals show poor results in cases involving strong reverberation, large distances between microphones and asynchronous recordings. Under similar conditions, a method based on cross-correlation of temporal envelopes of the signals delivers a delay estimation of acceptable quality. This method and its properties are described and investigated in detail, including its limits of applicability. The method’s optimal parameter estimation and a comparison with other known methods of time delay estimation are also provided. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cross-correlation" title="cross-correlation">cross-correlation</a>, <a href="https://publications.waset.org/abstracts/search?q=delay%20estimation" title=" delay estimation"> delay estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20envelope" title=" signal envelope"> signal envelope</a>, <a href="https://publications.waset.org/abstracts/search?q=signal%20processing" title=" signal processing"> signal processing</a> </p> <a href="https://publications.waset.org/abstracts/2280/time-delay-estimation-using-signal-envelopes-for-synchronisation-of-recordings" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2280.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">485</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22138</span> A Low-Latency Quadratic Extended Domain Modular Multiplier for Bilinear Pairing Based on Non-Least Positive Multiplication</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yulong%20Jia">Yulong Jia</a>, <a href="https://publications.waset.org/abstracts/search?q=Xiang%20Zhang"> Xiang Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Ziyuan%20Wu"> Ziyuan Wu</a>, <a href="https://publications.waset.org/abstracts/search?q=Shiji%20Hu"> Shiji Hu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The calculation of bilinear pairing is the core of the SM9 algorithm, which relies on the underlying prime domain algorithm and the quadratic extension domain algorithm. Among the field algorithms, modular multiplication operation is the most time-consuming part. Therefore, the underlying modular multiplication algorithm is optimized to maximize the operation speed of bilinear pairings. This paper uses a modular multiplication method based on non-least positive (NLP) combined with Karatsuba and schoolbook multiplication to improve the Montgomery algorithm. At the same time, according to the characteristics of multiplication operation in the quadratic extension domain, a quadratic extension domain FP2-NLP modular multiplication algorithm for bilinear pairings is proposed, which effectively reduces the operation time of modular multiplication in the quadratic extension domain. The sub-expanded domain Fp₂ -NLP modular multiplication algorithm effectively reduces the operation time of modular multiplication under the second-expanded domain. The multiplication unit in the quadratic extension domain is implemented using SMIC55nm process, and two different implementation architectures are designed to cope with different application scenarios. Compared with the existing related literature, The output latency of this design can reach a minimum of 15 cycles. The shortest time for calculating the (AB+CD)r⁻¹ mod form is 37.5ns, and the comprehensive area-time product (AT) is 11400. The final R-ate pairing algorithm hardware accelerator consumes 2670k equivalent logic gates and 1.8ms computing time in 55nm process. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=sm9" title="sm9">sm9</a>, <a href="https://publications.waset.org/abstracts/search?q=hardware" title=" hardware"> hardware</a>, <a href="https://publications.waset.org/abstracts/search?q=NLP" title=" NLP"> NLP</a>, <a href="https://publications.waset.org/abstracts/search?q=Montgomery" title=" Montgomery"> Montgomery</a> </p> <a href="https://publications.waset.org/abstracts/194787/a-low-latency-quadratic-extended-domain-modular-multiplier-for-bilinear-pairing-based-on-non-least-positive-multiplication" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/194787.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">5</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22137</span> Lithium-Ion Battery State of Charge Estimation Using One State Hysteresis Model with Nonlinear Estimation Strategies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Farag">Mohammed Farag</a>, <a href="https://publications.waset.org/abstracts/search?q=Mina%20Attari"> Mina Attari</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Andrew%20Gadsden"> S. Andrew Gadsden</a>, <a href="https://publications.waset.org/abstracts/search?q=Saeid%20R.%20Habibi"> Saeid R. Habibi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Battery state of charge (SOC) estimation is an important parameter as it measures the total amount of electrical energy stored at a current time. The SOC percentage acts as a fuel gauge if it is compared with a conventional vehicle. Estimating the SOC is, therefore, essential for monitoring the amount of useful life remaining in the battery system. This paper looks at the implementation of three nonlinear estimation strategies for Li-Ion battery SOC estimation. One of the most common behavioral battery models is the one state hysteresis (OSH) model. The extended Kalman filter (EKF), the smooth variable structure filter (SVSF), and the time-varying smoothing boundary layer SVSF are applied on this model, and the results are compared. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=state%20of%20charge%20estimation" title="state of charge estimation">state of charge estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=battery%20modeling" title=" battery modeling"> battery modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=one-state%20hysteresis" title=" one-state hysteresis"> one-state hysteresis</a>, <a href="https://publications.waset.org/abstracts/search?q=filtering%20and%20estimation" title=" filtering and estimation"> filtering and estimation</a> </p> <a href="https://publications.waset.org/abstracts/68017/lithium-ion-battery-state-of-charge-estimation-using-one-state-hysteresis-model-with-nonlinear-estimation-strategies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68017.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">444</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22136</span> Forecasting the Volatility of Geophysical Time Series with Stochastic Volatility Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Maria%20C.%20Mariani">Maria C. Mariani</a>, <a href="https://publications.waset.org/abstracts/search?q=Md%20Al%20Masum%20Bhuiyan"> Md Al Masum Bhuiyan</a>, <a href="https://publications.waset.org/abstracts/search?q=Osei%20K.%20Tweneboah"> Osei K. Tweneboah</a>, <a href="https://publications.waset.org/abstracts/search?q=Hector%20G.%20Huizar"> Hector G. Huizar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work is devoted to the study of modeling geophysical time series. A stochastic technique with time-varying parameters is used to forecast the volatility of data arising in geophysics. In this study, the volatility is defined as a logarithmic first-order autoregressive process. We observe that the inclusion of log-volatility into the time-varying parameter estimation significantly improves forecasting which is facilitated via maximum likelihood estimation. This allows us to conclude that the estimation algorithm for the corresponding one-step-ahead suggested volatility (with ±2 standard prediction errors) is very feasible since it possesses good convergence properties. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Augmented%20Dickey%20Fuller%20Test" title="Augmented Dickey Fuller Test">Augmented Dickey Fuller Test</a>, <a href="https://publications.waset.org/abstracts/search?q=geophysical%20time%20series" title=" geophysical time series"> geophysical time series</a>, <a href="https://publications.waset.org/abstracts/search?q=maximum%20likelihood%20estimation" title=" maximum likelihood estimation"> maximum likelihood estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20volatility%20model" title=" stochastic volatility model"> stochastic volatility model</a> </p> <a href="https://publications.waset.org/abstracts/75110/forecasting-the-volatility-of-geophysical-time-series-with-stochastic-volatility-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75110.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">315</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22135</span> Hybrid Subspace Approach for Time Delay Estimation in MIMO Systems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mojtaba%20Saeedinezhad">Mojtaba Saeedinezhad</a>, <a href="https://publications.waset.org/abstracts/search?q=Sarah%20Yousefi"> Sarah Yousefi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we present a hybrid subspace approach for Time Delay Estimation (TDE) in multivariable systems. While several methods have been proposed for time delay estimation in SISO systems, delay estimation in MIMO systems were always a big challenge. In these systems the existing TDE methods have significant limitations because most of procedures are just based on system response estimation or correlation analysis. We introduce a new hybrid method for TDE in MIMO systems based on subspace identification and explicit output error method; and compare its performance with previously introduced procedures in presence of different noise levels and in a statistical manner. Then the best method is selected with multi objective decision making technique. It is shown that the performance of new approach is much better than the existing methods, even in low signal-to-noise conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=system%20identification" title="system identification">system identification</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20delay%20estimation" title=" time delay estimation"> time delay estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=ARX" title=" ARX"> ARX</a>, <a href="https://publications.waset.org/abstracts/search?q=OE" title=" OE"> OE</a>, <a href="https://publications.waset.org/abstracts/search?q=merit%20ratio" title=" merit ratio"> merit ratio</a>, <a href="https://publications.waset.org/abstracts/search?q=multi%20variable%20decision%20making" title=" multi variable decision making"> multi variable decision making</a> </p> <a href="https://publications.waset.org/abstracts/48722/hybrid-subspace-approach-for-time-delay-estimation-in-mimo-systems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48722.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">346</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22134</span> Continuous-Time Analysis And Performance Assessment For Digital Control Of High-Frequency Switching Synchronous Dc-Dc Converter</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rihab%20Hamdi">Rihab Hamdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Amel%20Hadri%20Hamida"> Amel Hadri Hamida</a>, <a href="https://publications.waset.org/abstracts/search?q=Ouafae%20Bennis"> Ouafae Bennis</a>, <a href="https://publications.waset.org/abstracts/search?q=Sakina%20Zerouali"> Sakina Zerouali</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper features a performance analysis and robustness assessment of a digitally controlled DC-DC three-cell buck converter associated in parallel, operating in continuous conduction mode (CCM), facing feeding parameters variation and loads disturbance. The control strategy relies on the continuous-time with an averaged modeling technique for high-frequency switching converter. The methodology is to modulate the complete design procedure, in regard to the existence of an instantaneous current operating point for designing the digital closed-loop, to the same continuous-time domain. Moreover, the adopted approach is to include a digital voltage control (DVC) technique, taking an account for digital control delays and sampling effects, which aims at improving efficiency and dynamic response and preventing generally undesired phenomena. The results obtained under load change, input change, and reference change clearly demonstrates an excellent dynamic response of the proposed technique, also as provide stability in any operating conditions, the eﬀectiveness is fast with a smooth tracking of the specified output voltage. Simulations studies in MATLAB/Simulink environment are performed to verify the concept. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=continuous%20conduction%20mode" title="continuous conduction mode">continuous conduction mode</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20control" title=" digital control"> digital control</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20multi-cells%20converter" title=" parallel multi-cells converter"> parallel multi-cells converter</a>, <a href="https://publications.waset.org/abstracts/search?q=performance%20analysis" title=" performance analysis"> performance analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20electronics" title=" power electronics"> power electronics</a> </p> <a href="https://publications.waset.org/abstracts/130482/continuous-time-analysis-and-performance-assessment-for-digital-control-of-high-frequency-switching-synchronous-dc-dc-converter" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/130482.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">150</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22133</span> A Packet Loss Probability Estimation Filter Using Most Recent Finite Traffic Measurements</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pyung%20Soo%20Kim">Pyung Soo Kim</a>, <a href="https://publications.waset.org/abstracts/search?q=Eung%20Hyuk%20Lee"> Eung Hyuk Lee</a>, <a href="https://publications.waset.org/abstracts/search?q=Mun%20Suck%20Jang"> Mun Suck Jang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A packet loss probability (PLP) estimation filter with finite memory structure is proposed to estimate the packet rate mean and variance of the input traffic process in real-time while removing undesired system and measurement noises. The proposed PLP estimation filter is developed under a weighted least square criterion using only the finite traffic measurements on the most recent window. The proposed PLP estimation filter is shown to have several inherent properties such as unbiasedness, deadbeat, robustness. A guideline for choosing appropriate window length is described since it can affect significantly the estimation performance. Using computer simulations, the proposed PLP estimation filter is shown to be superior to the Kalman filter for the temporarily uncertain system. One possible explanation for this is that the proposed PLP estimation filter can have greater convergence time of a filtered estimate as the window length M decreases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=packet%20loss%20probability%20estimation" title="packet loss probability estimation">packet loss probability estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=finite%20memory%20filter" title=" finite memory filter"> finite memory filter</a>, <a href="https://publications.waset.org/abstracts/search?q=infinite%20memory%20filter" title=" infinite memory filter"> infinite memory filter</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalman%20filter" title=" Kalman filter"> Kalman filter</a> </p> <a href="https://publications.waset.org/abstracts/9519/a-packet-loss-probability-estimation-filter-using-most-recent-finite-traffic-measurements" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9519.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">672</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22132</span> Comparative Dielectric Properties of 1,2-Dichloroethane with n-Methylformamide and n,n-Dimethylformamide Using Time Domain Reflectometry Technique in Microwave Frequency</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Shagufta%20Tabassum">Shagufta Tabassum</a>, <a href="https://publications.waset.org/abstracts/search?q=V.%20P.%20Pawar"> V. P. Pawar</a>, <a href="https://publications.waset.org/abstracts/search?q=jr."> jr.</a>, <a href="https://publications.waset.org/abstracts/search?q=G.%20N.%20Shinde"> G. N. Shinde</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The study of dielectric relaxation properties of polar liquids in the binary mixture has been carried out at 10, 15, 20 and 25 ºC temperatures for 11 different concentrations using time domain reflectometry technique. The dielectric properties of a solute-solvent mixture of polar liquids in the frequency range of 10 MHz to 30 GHz gives the information regarding formation of monomers and multimers and also an interaction between the molecules of the liquid mixture under study. The dielectric parameters have been obtained by the least squares fit method using the Debye equation characterized by a single relaxation time without relaxation time distribution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=excess%20properties" title="excess properties">excess properties</a>, <a href="https://publications.waset.org/abstracts/search?q=relaxation%20time" title=" relaxation time"> relaxation time</a>, <a href="https://publications.waset.org/abstracts/search?q=static%20dielectric%20constant" title=" static dielectric constant"> static dielectric constant</a>, <a href="https://publications.waset.org/abstracts/search?q=and%20time%20domain%20reflectometry%20technique" title=" and time domain reflectometry technique"> and time domain reflectometry technique</a> </p> <a href="https://publications.waset.org/abstracts/110068/comparative-dielectric-properties-of-12-dichloroethane-with-n-methylformamide-and-nn-dimethylformamide-using-time-domain-reflectometry-technique-in-microwave-frequency" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110068.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">155</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22131</span> Vibrations of Springboards: Mode Shape and Time Domain Analysis </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Stefano%20Frassinelli">Stefano Frassinelli</a>, <a href="https://publications.waset.org/abstracts/search?q=Alessandro%20Niccolai"> Alessandro Niccolai</a>, <a href="https://publications.waset.org/abstracts/search?q=Riccardo%20E.%20Zich"> Riccardo E. Zich</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Diving is an important Olympic sport. In this sport, the effective performance of the athlete is related to his capability to interact correctly with the springboard. In fact, the elevation of the jump and the correctness of the dive are influenced by the vibrations of the board. In this paper, the vibrations of the springboard will be analyzed by means of typical tools for vibration analysis: Firstly, a modal analysis will be done on two different models of the springboard, then, these two model and another one will be analyzed with a time analysis, done integrating the equations of motion od deformable bodies. All these analyses will be compared with experimental data measured on a real springboard by means of a 6-axis accelerometer; these measurements are aimed to assess the models proposed. The acquired data will be analyzed both in frequency domain and in time domain. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=springboard%20analysis" title="springboard analysis">springboard analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=modal%20analysis" title=" modal analysis"> modal analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20domain%20analysis" title=" time domain analysis"> time domain analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=vibrations" title=" vibrations"> vibrations</a> </p> <a href="https://publications.waset.org/abstracts/61559/vibrations-of-springboards-mode-shape-and-time-domain-analysis" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/61559.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">460</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22130</span> Assisted Prediction of Hypertension Based on Heart Rate Variability and Improved Residual Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yong%20Zhao">Yong Zhao</a>, <a href="https://publications.waset.org/abstracts/search?q=Jian%20He"> Jian He</a>, <a href="https://publications.waset.org/abstracts/search?q=Cheng%20Zhang"> Cheng Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=feature%20extraction" title="feature extraction">feature extraction</a>, <a href="https://publications.waset.org/abstracts/search?q=heart%20rate%20variability" title=" heart rate variability"> heart rate variability</a>, <a href="https://publications.waset.org/abstracts/search?q=hypertension" title=" hypertension"> hypertension</a>, <a href="https://publications.waset.org/abstracts/search?q=residual%20networks" title=" residual networks"> residual networks</a> </p> <a href="https://publications.waset.org/abstracts/165227/assisted-prediction-of-hypertension-based-on-heart-rate-variability-and-improved-residual-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/165227.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">105</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22129</span> Robust Model Predictive Controller for Uncertain Nonlinear Wheeled Inverted Pendulum Systems: A Tube-Based Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tran%20Gia%20Khanh">Tran Gia Khanh</a>, <a href="https://publications.waset.org/abstracts/search?q=Dao%20Phuong%20Nam"> Dao Phuong Nam</a>, <a href="https://publications.waset.org/abstracts/search?q=Do%20Trong%20Tan"> Do Trong Tan</a>, <a href="https://publications.waset.org/abstracts/search?q=Nguyen%20Van%20Huong"> Nguyen Van Huong</a>, <a href="https://publications.waset.org/abstracts/search?q=Mai%20Xuan%20Sinh"> Mai Xuan Sinh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work presents the problem of tube-based robust model predictive controller for a class of continuous-time systems in the presence of input disturbances. The main objective is to point out the state trajectory of closed system being maintained inside a sequence of tubes. An estimation of attraction region of the closed system is pointed out based on input state stability (ISS) theory and linearized model in each time interval. The theoretical analysis and simulation results demonstrate the performance of the proposed algorithm for a wheeled inverted pendulum system. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=input%20state%20stability%20%28ISS%29" title="input state stability (ISS)">input state stability (ISS)</a>, <a href="https://publications.waset.org/abstracts/search?q=tube-based%20robust%20MPC" title=" tube-based robust MPC"> tube-based robust MPC</a>, <a href="https://publications.waset.org/abstracts/search?q=continuous-time%20nonlinear%20systems" title=" continuous-time nonlinear systems"> continuous-time nonlinear systems</a>, <a href="https://publications.waset.org/abstracts/search?q=wheeled%20inverted%20pendulum" title=" wheeled inverted pendulum"> wheeled inverted pendulum</a> </p> <a href="https://publications.waset.org/abstracts/80455/robust-model-predictive-controller-for-uncertain-nonlinear-wheeled-inverted-pendulum-systems-a-tube-based-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/80455.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">220</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22128</span> Approximation of the Time Series by Fractal Brownian Motion</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Valeria%20Bondarenko">Valeria Bondarenko</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose two problems related to fractal Brownian motion. First problem is simultaneous estimation of two parameters, Hurst exponent and the volatility, that describe this random process. Numerical tests for the simulated fBm provided an efficient method. Second problem is approximation of the increments of the observed time series by a power function by increments from the fractional Brownian motion. Approximation and estimation are shown on the example of real data, daily deposit interest rates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=fractional%20Brownian%20motion" title="fractional Brownian motion">fractional Brownian motion</a>, <a href="https://publications.waset.org/abstracts/search?q=Gausssian%20processes" title=" Gausssian processes"> Gausssian processes</a>, <a href="https://publications.waset.org/abstracts/search?q=approximation" title=" approximation"> approximation</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20series" title=" time series"> time series</a>, <a href="https://publications.waset.org/abstracts/search?q=estimation%20of%20properties%20of%20the%20model" title=" estimation of properties of the model"> estimation of properties of the model</a> </p> <a href="https://publications.waset.org/abstracts/4285/approximation-of-the-time-series-by-fractal-brownian-motion" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4285.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">376</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22127</span> Estimating Lost Digital Video Frames Using Unidirectional and Bidirectional Estimation Based on Autoregressive Time Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Navid%20Daryasafar">Navid Daryasafar</a>, <a href="https://publications.waset.org/abstracts/search?q=Nima%20Farshidfar"> Nima Farshidfar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article, we make attempt to hide error in video with an emphasis on the time-wise use of autoregressive (AR) models. To resolve this problem, we assume that all information in one or more video frames is lost. Then, lost frames are estimated using analogous Pixels time information in successive frames. Accordingly, after presenting autoregressive models and how they are applied to estimate lost frames, two general methods are presented for using these models. The first method which is the same standard method of autoregressive models estimates lost frame in unidirectional form. Usually, in such condition, previous frames information is used for estimating lost frame. Yet, in the second method, information from the previous and next frames is used for estimating the lost frame. As a result, this method is known as bidirectional estimation. Then, carrying out a series of tests, performance of each method is assessed in different modes. And, results are compared. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=error%20steganography" title="error steganography">error steganography</a>, <a href="https://publications.waset.org/abstracts/search?q=unidirectional%20estimation" title=" unidirectional estimation"> unidirectional estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=bidirectional%20estimation" title=" bidirectional estimation"> bidirectional estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=AR%20linear%20estimation" title=" AR linear estimation"> AR linear estimation</a> </p> <a href="https://publications.waset.org/abstracts/14175/estimating-lost-digital-video-frames-using-unidirectional-and-bidirectional-estimation-based-on-autoregressive-time-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14175.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">539</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22126</span> Aliasing Free and Additive Error in Spectra for Alpha Stable Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=R.%20Sabre">R. Sabre</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work focuses on the symmetric alpha stable process with continuous time frequently used in modeling the signal with indefinitely growing variance, often observed with an unknown additive error. The objective of this paper is to estimate this error from discrete observations of the signal. For that, we propose a method based on the smoothing of the observations via Jackson polynomial kernel and taking into account the width of the interval where the spectral density is non-zero. This technique allows avoiding the “Aliasing phenomenon” encountered when the estimation is made from the discrete observations of a process with continuous time. We have studied the convergence rate of the estimator and have shown that the convergence rate improves in the case where the spectral density is zero at the origin. Thus, we set up an estimator of the additive error that can be subtracted for approaching the original signal without error. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectral%20density" title="spectral density">spectral density</a>, <a href="https://publications.waset.org/abstracts/search?q=stable%20processes" title=" stable processes"> stable processes</a>, <a href="https://publications.waset.org/abstracts/search?q=aliasing" title=" aliasing"> aliasing</a>, <a href="https://publications.waset.org/abstracts/search?q=non%20parametric" title=" non parametric"> non parametric</a> </p> <a href="https://publications.waset.org/abstracts/110786/aliasing-free-and-additive-error-in-spectra-for-alpha-stable-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/110786.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22125</span> Remaining Useful Life Estimation of Bearings Based on Nonlinear Dimensional Reduction Combined with Timing Signals</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zhongmin%20Wang">Zhongmin Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Wudong%20Fan"> Wudong Fan</a>, <a href="https://publications.waset.org/abstracts/search?q=Hengshan%20Zhang"> Hengshan Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Yimin%20Zhou"> Yimin Zhou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=continuous%20wavelet%20transform" title="continuous wavelet transform">continuous wavelet transform</a>, <a href="https://publications.waset.org/abstracts/search?q=convolution%20neural%20net-work" title=" convolution neural net-work"> convolution neural net-work</a>, <a href="https://publications.waset.org/abstracts/search?q=gated%20recurrent%20unit" title=" gated recurrent unit"> gated recurrent unit</a>, <a href="https://publications.waset.org/abstracts/search?q=health%20indicators" title=" health indicators"> health indicators</a>, <a href="https://publications.waset.org/abstracts/search?q=remaining%20useful%20life" title=" remaining useful life"> remaining useful life</a> </p> <a href="https://publications.waset.org/abstracts/108324/remaining-useful-life-estimation-of-bearings-based-on-nonlinear-dimensional-reduction-combined-with-timing-signals" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108324.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">133</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=continuous%20time%20domain%20estimation&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=continuous%20time%20domain%20estimation&page=3">3</a></li> <li class="page-item"><a class="page-link" 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