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 7
RAIL-5G: A Challenging Real-World Dataset and Benchmark for AI-Based 5G Indoor Localization
Reliable radio-based indoor localization is essential for industrial automation, yet existing methods are often evaluated in environments that do not fully reflect the severe multipath and…NeuroAct: Advancing EEG Analysis and Decoding via Dual-Loop Autonomous Research
EEG analysis and decoding underpin brain-computer interfaces, cognitive assessment, and sleep monitoring.Reliability-Preserving Compression for Deployable Medical Image Segmentation
Post-training compression of pretrained medical segmentation models commonly uses quantization, pruning, or distillation to reduce model size and computational cost.Is User Calibration Still Necessary for Continuous Myoelectric Control? A Closed-Loop Comparison of Calibration-Free Controllers
The need for user-specific calibration remains an often-cited barrier to widespread adoption of myoelectric control.Recurrent Temporal Restricted Boltzmann Machines as Unsupervised Encoders for Biomechanical Movement Sequences
Biomechanical movement recordings are continuous, high-dimensional time series, and analyzing them without manually labeling them requires representations that capture how movements evolve over time.PASS: A Trustworthy Precision Approach Simulation System for CAT III Integrity Algorithm Development
For fixed-wing aircraft, reliable localization during approach and landing is critical to flight safety.Beyond Latent Personalization: Integrating HRV-Conditioned Personalization via LLM for Interpretable Stress Detection
Stress detection based on heart rate variability (HRV) has received increasing attention.GRAFT-EEG: Gauge-Aware Physical Field Transport for Cross-Dataset Motor-Imagery EEG
Cross-dataset EEG decoding often treats montage, reference, and active-sensor changes as representation shift, although they also alter the observation operator.TriRouter: Sparse-to-Dense Electrode-Space Routing for Robust EEG Motor Imagery Decoding
Motor imagery brain-computer interfaces require reliable decoding from multichannel EEG, but practical acquisition often yields sparse or corrupted electrode montages.ECG-SDI: Single-lead Electrocardiogram Enables Continuous Sleep Depth Index Profiling and Scalable Digital Biomarkers for Sleep Health
Conventional sleep staging provides a coarse-grained representation that obscures within-stage depth variation.Sequence-to-Sequence Neural Surrogate Modeling of Transient Responses in High-Speed Links with Variable Design Parameters
This paper presents sequence-to-sequence (seq2seq) neural surrogates for high-speed transient response modeling and signal integrity analysis in fixed and variable design parameter spaces.GraphBEAT: Graph-based Bucketized Event Aggregation Over Time for Early Risk Stratification of Gastrointestinal Cancers
Longitudinal electronic health records (EHRs) contain complementary diagnostic and laboratory information about patient health.Generative adversarial networks with Monte Carlo dropout uncertainty quantification for structural health monitoring: Fibre Bragg grating data augmentation comparison in Hawk T1A aircraft
The signal generation capabilities of a novel data augmentation framework are examined in aerospace structures.An Agentic ENF Framework for Forensic Video Authentication Against Generative AI
Generative models now synthesise video that is hard to distinguish from genuine footage, and learned detectors that key on a generator's artefacts degrade sharply on unseen models.Train to Stitch: Topology-Preserving Regularization for Interoperable Representations
As large, powerful pre-trained models become more prevalent, there is growing interest in developing methods that allow different neural networks to be seamlessly combined with little or no direct…ONCship: A Large-Scale Underwater Acoustic Corpus for Ship Recognition
Recent advances in deep learning have significantly improved underwater acoustic vessel recognition.DeepPV-MRF: End-to-End Partial-Volume Fraction Estimation from MR Fingerprinting Time Series
Estimating subvoxel tissue fractions from magnetic resonance fingerprinting (MRF) is challenging.Exact Cap Response and Aperture Selection for Molecular Communication under Aligned Drift
Spatial reception under directed molecule transport requires balancing useful molecule capture against intersymbol interference (ISI).FlowSep-RF: Rectified Flow Matching for Single-Channel Radio-Frequency Signal Separation
Single-channel radio-frequency (RF) signal separation is important for interference mitigation when a signal of interest overlaps with a co-channel interferer in time and frequency.Analog RF Computing for Integrated Data and AI Flows Over Wireless Networks
Many resource-constrained edge devices require artificial intelligence (AI) services but are not powerful enough to store or execute neural networks (NNs).