Electrical Engineering and Systems Science

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(Nov)</option> <option value="12" >12 (Dec)</option> </select> <select id="catchup_year"> <option value="2025">2025</option> <option value="2024">2024</option> </select> <input type="hidden" id="date" name="date" /> , view results <select name="include_abs"> <option value="False" selected> without </option> <option value="True" > with </option> </select> abstracts <input type="submit" value="Go"/> </form> </li> <li><b>Search</b> within the <a href="https://arxiv.org/search/eess">eess archive</a></li> <li>Article statistics by year:<br> <a href="/year/eess/2025">2025</a> <a href="/year/eess/2024">2024</a> <a href="/year/eess/2023">2023</a> <a href="/year/eess/2022">2022</a> <a href="/year/eess/2021">2021</a> <a href="/year/eess/2020">2020</a> <a href="/year/eess/2019">2019</a> <a href="/year/eess/2018">2018</a> <a href="/year/eess/2017">2017</a> </li> </ul> <h2>Categories within Electrical Engineering and Systems Science</h2> <ul> <li><b>eess.AS - Audio and Speech Processing</b> (<a href="/list/eess.AS/new">new</a>, <a href="/list/eess.AS/recent">recent</a>, <a href="/list/eess.AS/current">current month</a>) <div class="description">Theory and methods for processing signals representing audio, speech, and language, and their applications. This includes analysis, synthesis, enhancement, transformation, classification and interpretation of such signals as well as the design, development, and evaluation of associated signal processing systems. Machine learning and pattern analysis applied to any of the above areas is also welcome. Specific topics of interest include: auditory modeling and hearing aids; acoustic beamforming and source localization; classification of acoustic scenes; speaker separation; active noise control and echo cancellation; enhancement; de-reverberation; bioacoustics; music signals analysis, synthesis and modification; music information retrieval; audio for multimedia and joint audio-video processing; spoken and written language modeling, segmentation, tagging, parsing, understanding, and translation; text mining; speech production, perception, and psychoacoustics; speech analysis, synthesis, and perceptual modeling and coding; robust speech recognition; speaker recognition and characterization; deep learning, online learning, and graphical models applied to speech, audio, and language signals; and implementation aspects ranging from system architecture to fast algorithms.</div> </li> <li><b>eess.IV - Image and Video Processing</b> (<a href="/list/eess.IV/new">new</a>, <a href="/list/eess.IV/recent">recent</a>, <a href="/list/eess.IV/current">current month</a>) <div class="description">Theory, algorithms, and architectures for the formation, capture, processing, communication, analysis, and display of images, video, and multidimensional signals in a wide variety of applications. Topics of interest include: mathematical, statistical, and perceptual image and video modeling and representation; linear and nonlinear filtering, de-blurring, enhancement, restoration, and reconstruction from degraded, low-resolution or tomographic data; lossless and lossy compression and coding; segmentation, alignment, and recognition; image rendering, visualization, and printing; computational imaging, including ultrasound, tomographic and magnetic resonance imaging; and image and video analysis, synthesis, storage, search and retrieval.</div> </li> <li><b>eess.SP - Signal Processing</b> (<a href="/list/eess.SP/new">new</a>, <a href="/list/eess.SP/recent">recent</a>, <a href="/list/eess.SP/current">current month</a>) <div class="description">Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.</div> </li> <li><b>eess.SY - Systems and Control</b> (<a href="/list/eess.SY/new">new</a>, <a href="/list/eess.SY/recent">recent</a>, <a href="/list/eess.SY/current">current month</a>) <div class="description">This section includes theoretical and experimental research covering all facets of automatic control systems. The section is focused on methods of control system analysis and design using tools of modeling, simulation and optimization. Specific areas of research include nonlinear, distributed, adaptive, stochastic and robust control in addition to hybrid and discrete event systems. Application areas include automotive and aerospace control systems, network control, biological systems, multiagent and cooperative control, robotics, reinforcement learning, sensor networks, control of cyber-physical and energy-related systems, and control of computing systems.</div> </li> </ul> <script> function catchupParamSelection(archive) { var day = document.getElementById('catchup_day').value.padStart(2, '0'); var month = document.getElementById('catchup_month').value.padStart(2, '0'); var year = document.getElementById('catchup_year').value; var combinedDate = `${year}-${month}-${day}`; document.getElementById('date').value = combinedDate; var categoryElement = document.getElementById('catchup_category'); var category = categoryElement ? categoryElement.value : ""; var subject; if (category && category !== "") { subject = category; } else { subject = archive; } document.getElementById('subject').value = subject } </script> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; 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