Engineering & Signals · Interdisciplinary & Society
Signal Processing
The newest papers in Signal Processing that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
429 papers, from 31 August 2026 to 5 November 2026: 360 arXiv preprints and 69 OpenAlex records.
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Newest papers, page 18
LoaDiff: Conditional Generation of Electricity Consumption Time Series for Energy Analytics
The energy transition is reshaping residential electricity consumption through the increasing adoption of distributed generation, electrified appliances, and demand-response programs.Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology
Clinical electroencephalography (EEG) data are valuable for healthcare research and for developing artificial intelligence (AI)-based clinical decision-support systems, but EEG recordings and…3D Point Splatting for mmWave Radar Novel View Synthesis
Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoint-tractable.BRIDGE-EEG: Bridging Self-Supervised Pretraining and Efficient Deployment for Cross-Dataset EEG Classification
The growing use of electroencephalography (EEG) motivates automated analysis that is accurate, transferable, and deployable on constrained hardware.CRFCAN: A Complex-Valued Cross-Domain Residual Network for Joint Channel and Phase Noise Estimation in Sub-THz OFDM Systems
In sub-terahertz (sub-THz) communications, the coupling of ultra-wide bandwidth and severe phase noise (PN) impairments renders conventional joint channel and PN estimation highly complex and…Fundamentals of Energy-Efficient Hardware Configurations for Wireless Links with Sleep Modes
In this paper, we examine the energy efficiency (EE) of a base station (BS) with multiple antennas.Modality-Decoupled Federated Learning for Privacy-Preserving Embodied Intelligence in 6G
Sixth-generation (6G) wireless networks are expected to provide a key infrastructure for large-scale embodied intelligence, where heterogeneous robots collaborate through low-latency connectivity…Efficient Graph Neural Networks for Multicarrier Wideband Hybrid Beamforming Optimization
6G wireless technology is poised to adopt higher and wider frequency bands, leveraging highly directional beamforming.Dimensionality Reduction for Hyperspectral Image Classification
This paper addresses the issue of supervised classification in the context of hyperspectral satellite images.Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems
More Electric Aircraft require fast and reliable monitoring of high-frequency electrical networks, yet most power quality disturbance and fault diagnosis methods are developed for conventional 50 or…Learning with Covariance Matrices: Principal Component Analysis Meets Learning with Graphs
This feature article provides an overview of the theoretical foundations for coVariance neural networks (VNNs), i.e., graph neural networks (GNNs) operating on covariance matrices as graphs.From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity
The ambitious requirements of sixth-generation (6G) networks are driving communication systems from reliable bit delivery toward meaning-aware and task-oriented connectivity.Do wind and solar curtail at negative electricity prices? Incentives and evidence across two decades of German renewable support schemes
In many power systems, wind and solar generation increasingly often exceeds electricity demand.Explicit Full-Spark Gabor Windows with Quantitative Phase Retrieval
We construct explicit algebraic finite Gabor windows that are simultaneously full spark and phase retrievable, with quantitative control of the self-ambiguity function.Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling
To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) exploits waveform superposition over…FedGenSC: Federated Generative Semantic Communication with Channel-Aware Adaptation
Integrating generative adversarial networks (GANs) into federated semantic communication (SemCom) is a natural progression, as generative priors can recover semantic fidelity under channel…Physics-Informed Deep Learning for False Ventricular Tachycardia Alarm Reduction in the ICU
False ventricular tachycardia (VT) alarms are a leading contributor to alarm fatigue in intensive care units.Reliable Near-Field Multi-User Positioning Informed by Two-Stage MUSIC
Near-field localization is a promising technique for high-resolution multi-user positioning in future wireless systems, but its performance is often degraded by scattering-induced coherent…MiNCE: Nonparametric, Strongly Consistent Confidence Envelopes for Band-Limited Functions and their Smoothed Spectra
Minimum-norm confidence envelope strategies offer a nonparametric approach to constructing nonasymptotic, simultaneous confidence regions for band-limited functions, exploiting the theory of…A Block Tensor Train Burer-Monteiro Framework for Low-Rank Quantum State Tomography
Quantum state tomography is a fundamental technique for estimating the state of a quantum system from measured data and plays a crucial role in evaluating the performance of quantum devices.