Research Article10.1016/j.sigpro.2025.110374A zero-dynamics attack detection scheme for networked power systems with electric vehicles: Watermark-based auxiliary function viewpointMar 01, 2026Signal ProcessingXinghua Liu + 5 more +5CiteListenSave
Research Article10.1016/j.sigpro.2025.110338Generalized nonnegative structured Kruskal tensor regressionMar 01, 2026Signal ProcessingXinjue Wang + 3 more +3This paper introduces Generalized Nonnegative Structured Kruskal Tensor Regression (NS-KTR), a novel tensor regression framework that enhances interpretability and performance through mode-specific hybrid regularization and nonnegativity constraints. Our approach accommodates both linear and logistic regression formulations for diverse response variables while addressing the structural heterogeneity inherent in multidimensional tensor data. We integrate fused LASSO, total variation, and ridge regularizers — each tailored to specific tensor modes — and develop an efficient alternating direction method of multipliers (ADMM)-based algorithm for parameter estimation. Comprehensive experiments on synthetic signals and real hyperspectral datasets demonstrate that NS-KTR consistently outperforms conventional tensor regression methods. The framework’s ability to preserve distinct structural characteristics across tensor dimensions while ensuring physical interpretability makes it especially suitable for applications in signal processing and hyperspectral image analysis. • NS-KTR: nonnegative structured Kruskal tensor regression with hybrid regularization. • Mode-specific regularization: LASSO, total variation, and ridge across tensor modes. • Unified framework supports linear and logistic regression for diverse responses. • ADMM-based optimization achieves superior accuracy with significant speedups.Read moreCiteListenSave
Research Article10.1016/j.sigpro.2025.110366HCCFNet: Hierarchical cross-modal and cross-granularity fusion network for infrared and visible image fusionMar 01, 2026Signal ProcessingTingen Yu + 4 more +4CiteListenSave
Research Article10.1016/j.sigpro.2025.110376Robust multi-source DOA tracking using Gaussian kernel smoothed MeMBer filter for generalized coprime arraysMar 01, 2026Signal ProcessingJingchao You + 4 more +4CiteListenSave
Research Article10.1016/j.sigpro.2026.110582Quaternion-based Unscented Kalman Filter for Robust Wrench Estimation of Human-UAV Physical InteractionMar 01, 2026Signal ProcessingHussein N Naser + 2 more +2CiteListenSave
Research Article510.1016/j.sigpro.2025.110375GLRT-based detectors with enhanced selectivity for mismatched signals through a random-signal approachMar 01, 2026Signal ProcessingWeijian Liu + 4 more +4CiteListenSave
Research Article110.1016/j.sigpro.2025.110180Compressive sensing based downlink channel estimation for mmWave systems using deep learning: Centralized or decentralizedFeb 01, 2026Signal ProcessingUsman Aslam + 4 more +4CiteListenSave
Research Article110.1016/j.sigpro.2025.110296A novel robust Student’s t scale mixture distribution based Kalman filterFeb 01, 2026Signal ProcessingBao Liu + 2 more +2CiteListenSave
Research Article110.1016/j.sigpro.2025.110229Error bound for two-dimensional DOA joint estimation in RIS assisted wireless networkFeb 01, 2026Signal ProcessingCuimin Pan + 3 more +3CiteListenSave
Research Article10.1016/j.sigpro.2025.110289Impact of communication link noise on distributed ATC stochastic optimization: Analysis and algorithmic enhancementsFeb 01, 2026Signal ProcessingYishu Peng + 4 more +4CiteListenSave