Distributed Compressed Sensing for biomedical signals

摘要

This paper presents a novel iterative greedy algorithm for Distributed Compressed Sensing (DCS) scenario based on backtracking technique, which is denoted by DCS-SAMP. The algorithm can reconstruct several input signals simultaneously, even when the measurements are contaminated with noise and without any prior information of their sparseness. It can provide a fast runtime while also offers comparably theoretical guarantees as the best optimization-based approach. This makes it as a promising candidate for many practical applications,such as Tele-Health or Telemedicine. Numerical experiments are performed to demonstrate the validity and high performance of the proposed DCS-SAMP algorithm for multichannel biomedical signals.