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 10
VM-ARRAYDPS: Virtual Microphone Augmented Diffusion Posterior Sampling for Unsupervised Blind Speech Separation
Blind Source Separation(BSS) is a fundamental problem in signal processing, aiming to separate multiple source signals from their mixtures without prior knowledge of the sources or the mixing process.Second-order optimization of variable projection SVM models and road abnormality detection
We introduce a novel second-order optimization framework for minimizing so-called variable projection functionals.A Proof-of-Concept Study of Weakly Supervised Labeling of Fine-Grained EEG Components for Artifact Attenuation
Electroencephalography (EEG) is highly susceptible to electromyographic (EMG) artifacts, whose temporal heterogeneity and spatial-spectral overlap with neural activity can leave mixed sources after…Similar Predictive Fit but Different Latent Dynamics: Characterizing Learned Dynamical Structure in Personalized Models of Brain Disorders
As AI models move toward clinical decision-making and personalized treatment, understanding \emph{what} a model learns is important beyond predictive accuracy alone.Self-Supervised Deconvolution of In-Air Sonar Images Using Sensor Ego-Motion
Broadband in-air sonar sensors with a sparse microphone array form images through delay-and-sum beamforming, which leaves high sidelobes and an angular resolution that degrades strongly towards the…CANDLE: Cortical Null-Space Decomposition for Noninvasive Brain Source Imaging
Electrophysiological source imaging (ESI) aims to estimate cortical source activity from noninvasive electrophysiological measurements such as electroencephalogram (EEG).Agentic Semantic Sensing for Resource-Adaptive AI-RAN
Semantic sensing (SemS) acquires task-relevant information rather than reconstructing complete physical information.Label-Efficient Deep Learning for ECG Delineation: A Multi-Dataset Benchmark against Widely Used Delineation Tools
Electrocardiogram (ECG) delineation, the identification of waveform boundaries, is a foundational step that translates raw ECG signals into clinically interpretable measurements.SNR-Gated LSTM-Conditioned Diffusion Model for MIMO Channel Estimation
Accurate and low latency channel estimation is critical for modern MIMO systems, particularly under mobility, where channels exhibit structured sparsity and strong temporal correlation.FlightMagNav: An Open Dataset and Probabilistic Map Learning and Validation Framework for Outdoor Magnetic Field-Based Positioning
Magnetic field-based positioning is a resilient positioning technology that requires no external infrastructure and is hard to jam at scale.BeatFlow-ECG: Rectified Flow for ECG Reconstruction from Indirect Wearable Signals
Continuous cardiac monitoring outside clinical settings requires signals that are both informative and practical to collect during daily life.Combining Improvements in Uplink AI-RAN
One of the major transformative factors in 6G will be the integration of Artificial Intelligence (AI) to become a native part of Radio Access Network (RAN).Inverse Cross-spectral Neural Networks for Multivariate Time Series
CoVariance Neural Networks and their extensions have emerged as effective tools for processing multivariate data, deriving graph shift operators directly from second-order statistics.Benchmarking Label-Revealed Online Updates for EEG BCI Decoding
Electroencephalography (EEG) signals drift over time, which can cause static brain-computer interface (BCI) models to degrade in practice.Adaptive Gait Biofeedback With Participant-Held-Out Modeling and Participant-Specific Updating in Chronic Ankle Instability
Adaptive gait biofeedback may support repeated practice in chronic ankle instability, but its evaluation must address model performance and human response.Artifact removal improves electrodermal waveforms but not downstream classification in a virtual-reality balance task
Artifact removal routinely precedes the classification of electrodermal activity (EDA), on the assumption that a cleaner signal supports a better decision.Kapture: Capturing Cardiac Dynamics with Koopman-Governed Learning for Efficient Radar-Based Electrocardiogram Recovery
Millimeter-wave (mmWave) radar enables unobtrusive, contactless electrocardiogram (ECG) reconstruction for cardiac monitoring.Performance Analysis of Multiparty GHZ-State Quantum Conference Key Agreement over Optical Fiber Channel
Quantum conference key agreement (QCKA) enables multiple spatially separated users to establish a common key with composable information-theoretic security by exploiting multipartite quantum…Lightweight Semantic EEG Foundation Model for Frozen Cross-Disorder Transfer
Large-scale EEG foundation models have demonstrated promising transferability across neurological disorders, but often require millions of parameters and substantial computational resources.One-Shot Beam Tracking for Stacked Intelligent Metasurfaces-Assisted LEO Broadcasting
This letter develops a physics-informed one-shot beam tracking method for stacked intelligent metasurface (SIM)-enabled low-Earth-orbit (LEO) links with $K$ users and an $L$-layer SIM with $N$…