Affiliation:
1. The School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing Jiangsu China
Abstract
AbstractGreedy pursuit algorithms are widely used in sparse signal processing for their computational efficiency. However, research on the reconstruction error properties is far from comprehensive. This paper derives the statistical properties of reconstruction error in greedy pursuit algorithms, including probability density function (PDF), expectation, and covariance. The reconstruction error follows a mixture distribution, which is composed of multiple multivariate random variables and weighted by the probability of support sets. The multivariate random variable obeys a truncated distribution that results from restricting the noise domain. The validity of the derivations is verified by using the orthogonal matching pursuit (OMP) algorithm as an example.
Funder
National Natural Science Foundation of China
Publisher
Institution of Engineering and Technology (IET)
Subject
Electrical and Electronic Engineering