Qwen Councils

Electrical Engineering and Systems Science

arXiv preprints from January 1, 2026 through July 20, 2026 — 12:03:37 EST

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Posted in eess.SP · 2026-01-21 · Zhiqing Wei, Yucong Du, Zhiyong Feng, Haotian Liu, Yanpeng Cui, Tao Zhang, Ying Zhou, Huici Wu

Integrated Sensing, Communication and Control enabled Agile UAV Swarm

Uncrewed aerial vehicle (UAV) swarms are pivotal in the applications such as disaster relief, aerial base station (BS) and logistics transportation. These scenarios require the capabilities in accurate sensing, efficient communication and flexible control for real-time and reliable task execution. However, sensing, communication and...

💬 0 commentsarXiv:2601.14783v1PDF
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Posted in eess.AS · 2026-01-21 · Tobias Raichle, Erfan Amini, Bin Yang

Test-Time Adaptation For Speech Enhancement Via Mask Polarization

Adapting speech enhancement (SE) models to unseen environments is crucial for practical deployments, yet test-time adaptation (TTA) for SE remains largely under-explored due to a lack of understanding of how SE models degrade under domain shifts. We observe that mask-based SE models lose confidence under domain shifts, with predicted...

💬 0 commentsarXiv:2601.14770v1PDF
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Posted in eess.SP · 2026-01-21 · Syed Luqman Shah, Nurul Huda Mahmood, Italo Atzeni

Improved GPR-Based CSI Acquisition via Spatial-Correlation Kernel

Accurate channel estimation with low pilot overhead and computational complexity is key to efficiently utilizing multi-antenna wireless systems. Motivated by the evolution from purely statistical descriptions toward physics- and geometry-aware propagation models, this work focuses on incorporating channel information into a Gaussian...

💬 0 commentsarXiv:2601.14759v2PDF
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Posted in eess.AS · 2026-01-21 · Steven Vander Eeckt, Hugo Van hamme

Inverse-Hessian Regularization for Continual Learning in ASR

Catastrophic forgetting remains a major challenge for continual learning (CL) in automatic speech recognition (ASR), where models must adapt to new domains without losing performance on previously learned conditions. Several CL methods have been proposed for ASR, and, recently, weight averaging - where models are averaged in a merging...

💬 0 commentsarXiv:2601.14751v1PDF
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Posted in eess.IV · 2026-01-21 · Xiang Li, Xueheng Li, Yu Wang, Xuanhua He, Zhangchi Hu, Weiwei Yu, Chengjun Xie

Q-Probe: Scaling Image Quality Assessment to High Resolution via Context-Aware Agentic Probing

Reinforcement Learning (RL) has empowered Multimodal Large Language Models (MLLMs) to achieve superior human preference alignment in Image Quality Assessment (IQA). However, existing RL-based IQA models typically rely on coarse-grained global views, failing to capture subtle local degradations in high-resolution scenarios. While...

💬 0 commentsarXiv:2601.15356v5PDF
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Posted in eess.AS · 2026-01-21 · Chun-Yi Kuan, Kai-Wei Chang, Hung-yi Lee

AQAScore: Evaluating Semantic Alignment in Text-to-Audio Generation via Audio Question Answering

Although text-to-audio generation has made remarkable progress in realism and diversity, the development of evaluation metrics has not kept pace. Widely-adopted approaches, typically based on embedding similarity like CLAPScore, effectively measure general relevance but remain limited in fine-grained semantic alignment and...

💬 0 commentsarXiv:2601.14728v1PDF
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Posted in eess.SY · 2026-01-21 · Zihao Ren, Lei Wang, Deming Yuan, Guodong Shi

Differential Privacy on Affine Manifolds: Geometrically Confined Privacy in Linear Dynamical Systems

In this paper, we present a comprehensive framework for differential privacy over affine manifolds and validate its usefulness in the contexts of differentially private cloud-based control and average consensus. We consider differential privacy mechanisms for linear queries when the input data are constrained to lie on affine...

💬 0 commentsarXiv:2601.14725v1PDF
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Posted in eess.AS · 2026-01-21 · Ruixing Ren, Junhui Zhao, Xiaoke Sun, Qiuping Li

NLP-Based Review for Toxic Comment Detection Tailored to the Chinese Cyberspace

With the in-depth integration of mobile Internet and widespread adoption of social platforms, user-generated content in the Chinese cyberspace has witnessed explosive growth. Among this content, the proliferation of toxic comments poses severe challenges to individual mental health, community atmosphere and social trust. Owing to the...

💬 0 commentsarXiv:2601.14721v1PDF
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Posted in eess.SP · 2026-01-21 · Lucas Giroto, Ândrei Camponogara, Yueheng Li, Jiayi Chen, Lukas Sigg, Thomas Zwick, Benjamin Nuss

Analysis of Sensing in OFDM-based ISAC under the Influence of Sampling Jitter

To enable integrated sensing and communication (ISAC) in cellular networks, a wide range of additional requirements and challenges are either imposed or become more critical. One such impairment is sampling jitter (SJ), which arises due to imperfections in the sampling instants of the clocks of digital-to-analog converters (DACs) and...

💬 0 commentsarXiv:2601.14881v1PDF
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Posted in eess.SY · 2026-01-21 · Lei Zheng, Luyao Zhang, Peiqi Yu, Yifan Sun, Sergio Grammatico, Jun Ma, Changliu Liu

Contingency Planning for Safety-Critical Autonomous Vehicles: A Review and Perspectives

Contingency planning is the architectural capability that enables autonomous vehicles (AVs) to anticipate and mitigate discrete, high-impact hazards, such as sensor outages and adversarial interactions. This paper presents a comprehensive survey of the field, synthesizing fragmented literature into a unified logic-conditioned hybrid...

💬 0 commentsarXiv:2601.14880v1PDF
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Posted in eess.SP · 2026-01-21 · Ran Yang, Ning Wei, Zheng Dong, Lin Zhang, Wanting Lyu, Yue Xiu, Ahmad Bazzi, Chadi Assi

Movable Antenna Empowered Covert Dual-Functional Radar-Communication

Movable antenna (MA) has emerged as a promising technology to flexibly reconfigure wireless channels by adjusting antenna placement. In this paper, we study a secured dual-functional radar-communication (DFRC) system aided by movable antennas. To enhance the communication security, we aim to maximize the achievable sum rate by jointly...

💬 0 commentsarXiv:2601.14868v2PDF
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Posted in eess.SP · 2026-01-21 · Maria A van Agthoven, Marek Polák, Jan Fiala, Claude Nelcy Ounounou, Petr Halada, Michael Palasser, Anne Briot-Dietsch, Alan Kádek, Kathrin Breuker, Petr Novák, Carlos Afonso, Marc-André Delsuc

Absorption mode broadband 2D MS for proteomics and metabolomics

Two-dimensional mass spectrometry (2D MS) is a method for tandem mass spectrometry that enables the correlation between precursor and fragment ions without the need for ion isolation. On a Fourier transform ion cyclotron resonance mass spectrometer, the phase correction functions for absorption mode data processing were found to be...

💬 0 commentsarXiv:2601.14820v1PDF
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Posted in eess.IV · 2026-01-21 · Yi Zhu, Razmig Kechichian, Raphaël Richert, Satoshi Ikehata, Sébastien Valette

High-Fidelity 3D Tooth Reconstruction by Fusing Intraoral Scans and CBCT Data via a Deep Implicit Representation

High-fidelity 3D tooth models are essential for digital dentistry, but must capture both the detailed crown and the complete root. Clinical imaging modalities are limited: Cone-Beam Computed Tomography (CBCT) captures the root but has a noisy, low-resolution crown, while Intraoral Scanners (IOS) provide a high-fidelity crown but no...

💬 0 commentsarXiv:2601.15358v1PDF
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Posted in eess.SY · 2026-01-21 · Jingwei Dong, André M. H. Teixeira

Stealthy bias injection attack detection based on Kullback-Leibler divergence in stochastic linear systems

This paper studies the design of detection observers against stealthy bias injection attacks in stochastic linear systems under Gaussian noise, considering adversaries that exploit noise and inject crafted bias signals into a subset of sensors in a slow and coordinated manner, thereby achieving malicious objectives while remaining...

💬 0 commentsarXiv:2601.14984v1PDF
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Posted in eess.SP · 2026-01-21 · Advaith Arun, Shiv Shankar, Dhivagar Baskaran, Klutto Milleth, Bhaskar Ramamurthi

Deep Learning assisted Port-Cycling based Channel Sounding for Precoder Estimation in Massive MIMO Arrays

Future wireless systems are expected to employ a substantially larger number of transmit ports for channel state information (CSI) estimation compared to current specifications. Although scaling ports improves spectral efficiency, it also increases the resource overhead to transmit reference signals across the time-frequency grid,...

💬 0 commentsarXiv:2601.14953v2PDF
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Posted in eess.AS · 2026-01-21 · Nicolás Arrieta Larraza, Niels de Koeijer

Fast-ULCNet: A fast and ultra low complexity network for single-channel speech enhancement

Single-channel speech enhancement algorithms are often used in resource-constrained embedded devices, where low latency and low complexity designs gain more importance. In recent years, researchers have proposed a wide variety of novel solutions to this problem. In particular, a recent deep learning model named ULCNet is among the...

💬 0 commentsarXiv:2601.14925v1PDF
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Posted in eess.SY · 2026-01-21 · Maiken Borud Omtveit, Qian Long, Valentin Chabaud, Marte Ruud-Olsen, Steinar Halsne, Tor-Christian Ystgaard

Electrical Design of a Clean Offshore Heat and Power (CleanOFF) Hub

This paper presents an innovative offshore solution where oil & gas platform clusters are powered by a wind farm and a hydrogen hub. The results show a feasible off-grid design as an alternative to conventional electrification solutions. To address the challenges of design and operation of such a system, a power system model of the...

💬 0 commentsarXiv:2601.15040v2PDF
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Posted in eess.SP · 2026-01-21 · Nipun Agarwal

Physical Layer Security in Massive MIMO: Challenges and Open Research Directions Against Passive Eavesdroppers

Massive Multiple-Input Multiple-Output (MIMO) has become a crucial enabling technology for 5G and beyond, providing previously unheard-of increases in energy and spectrum efficiency. It is still difficult to guarantee secure communication in these systems, particularly when it comes to passive eavesdroppers whose base station is...

💬 0 commentsarXiv:2601.15024v1PDF
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Posted in eess.SP · 2026-01-21 · Nipun Agarwal

Alternative Shapes of Modulation Schemes Detailed Exposition and Simulation Methodology

Modulation constellation design is a core challenge in digital communications, especially under stringent demands on spectral efficiency, robustness, and energy consumption. Classical schemes like PSK and QAM, while analytically tractable, often lose optimality under realistic channels and nonlinear hardware constraints. This paper...

💬 0 commentsarXiv:2601.15004v1PDF
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Posted in eess.IV · 2026-01-21 · K. Punnam Chandar, Y. Ravi Kumar

Filtered 2D Contour-Based Reconstruction of 3D STL Model from CT-DICOM Images

Reconstructing a 3D Stereo-lithography (STL) Model from 2D Contours of scanned structure in Digital Imaging and Communication in Medicine (DICOM) images is crucial to understand the geometry and deformity. Computed Tomography (CT) images are processed to enhance the contrast, reduce the noise followed by smoothing. The processed CT...

💬 0 commentsarXiv:2601.14997v1PDF
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Posted in eess.SP · 2026-01-21 · Victoria Palhares, Artjom Grudnitsky, Silvio Mandelli

Weather Estimation for Integrated Sensing and Communication

One of the key features of sixth-generation (6G) mobile communications will be integrated sensing and communication (ISAC). While the main goal of ISAC in standardization efforts is to detect objects, the byproducts of radar operations can be used to enable new services in 6G, such as weather sensing. Even though weather radars are...

💬 0 commentsarXiv:2601.15145v2PDF
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Posted in eess.SY · 2026-01-21 · Natanon Tongamrak, Kannapha Amaruchkul, Wijarn Wangdee, Jitkomut Songsiri

Stochastic EMS for Optimal 24/7 Carbon-Free Energy Operations

This paper proposes a two-stage stochastic optimization formulation to determine optimal operation and procurement plans for achieving a 24/7 carbon-free energy (CFE) compliance at minimized cost. The system in consideration follows primary energy technologies in Thailand including solar power, battery storage, and a diverse portfolio...

💬 0 commentsarXiv:2601.15135v1PDF
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Posted in eess.SP · 2026-01-21 · Robin Rajamäki, Visa Koivunen

Sparse Sensor Arrays for Active Sensing: Models, Configurations and Applications

This chapter focuses on active sensing using sparse arrays. In active sensing applications, such as radar, sonar, wireless communications, and medical ultrasound, a collection of sensors probes the environment by emitting self-generated energy. A key benefit of such active multi-sensor arrays is their ability to focus and steer energy...

💬 0 commentsarXiv:2601.15126v1PDF
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Posted in eess.IV · 2026-01-21 · Md Mahmudul Hoque, Md Mehedi Hassain, Muntakimur Rahaman, Md. Towhidul Islam, Shaista Rani, Md Sharif Mollah

Vision Models for Medical Imaging: A Hybrid Approach for PCOS Detection from Ultrasound Scans

Polycystic Ovary Syndrome (PCOS) is the most familiar endocrine illness in women of reproductive age. Many Bangladeshi women suffer from PCOS disease in their older age. The aim of our research is to identify effective vision-based medical image analysis techniques and evaluate hybrid models for the accurate detection of PCOS. We...

💬 0 commentsarXiv:2601.15119v1PDF
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Posted in eess.SY · 2026-01-21 · A. Vaca, J. Gutierrez Florensa, F. Milano

Instantaneous Frequency in Power Systems using the Teager-Kaiser Energy Operator

This letter develops an instantaneous-frequency (IF) local estimator calculated with the complex Teager-Kaiser energy operator (CTKEO) and the dynamic-signal identity. The contribution is a novel CTKEO-based IF expression that makes the envelope-curvature terms explicit, thus correcting the bias that affects conventional estimators...

💬 0 commentsarXiv:2601.15099v2PDF