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Bibliographic Details
Main Authors: Bian, Ning, Sun, Zhong-Feng, Zhao, Yun-Bin, Zhou, Jin-Chuan, Meng, Nan
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2602.15880
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Table of Contents:
  • Nonnegative sparse signal recovery has been extensively studied due to its broad applications. Recent work has integrated rectified linear unit (ReLU) techniques to enhance existing recovery algorithms. We merge Newton-type thresholding with ReLU-based approaches to propose two algorithms: Newton-Direction-Based ReLU-Thresholding (NDRT) and its enhanced variant, Newton-Direction-Based ReLU-Thresholding Pursuit (NDRTP). Theoretical analysis iindicates that both algorithms can guarantee exact recovery of nonnegative sparse signals when the measurement matrix satisfies a certain condition.. Numerical experiments demonstrate NDRTP achieves competitive performance compared to several existing methods in both noisy and noiseless scenarios.