Verification-Based Interval-Passing Algorithm for Compressed Sensing

TL;DR

This paper introduces a verification-based interval-passing algorithm for improved iterative reconstruction of nonnegative sparse signals in compressed sensing, outperforming existing IP and verification algorithms.

Contribution

The paper presents a novel combined verification-based interval-passing algorithm that enhances reconstruction performance over traditional methods.

Findings

The proposed algorithm always outperforms IP and verification algorithms.

Simulation results confirm the superior performance of the new method.

The algorithm effectively reconstructs nonnegative sparse signals with higher accuracy.

Abstract

We propose a verification-based Interval-Passing (IP) algorithm for iteratively reconstruction of nonnegative sparse signals using parity check matrices of low-density parity check (LDPC) codes as measurement matrices. The proposed algorithm can be considered as an improved IP algorithm by further incorporation of the mechanism of verification algorithm. It is proved that the proposed algorithm performs always better than either the IP algorithm or the verification algorithm. Simulation results are also given to demonstrate the superior performance of the proposed algorithm.