Paper Title:
Improvement of Gaussian Random Measurement Matrices in Compressed Sensing
  Abstract

Compressed sensing seeks to recover a sparse or compressible signal from a small number of linear and non-adaptive measurements. Gaussian random matrix is a kind of fundamental measurement matrices, but its performance isn’t perfect because of more errors in recovery. This paper studies a new kind of matrix based on improving Gaussian random matrices. Measure sparse signals with improved matrices and recover original signals with orthogonal matching pursuit. Numerical experiments showed that the quality of recovered signal by improved measurement matrices is better than Gaussian random matrices.

  Info
Periodical
Advanced Materials Research (Volumes 301-303)
Chapter
Chapter 1: Material Science and Technology
Edited by
Riza Esa and Yanwen Wu
Pages
245-250
DOI
10.4028/www.scientific.net/AMR.301-303.245
Citation
B. Wang, S. X. Ma, "Improvement of Gaussian Random Measurement Matrices in Compressed Sensing", Advanced Materials Research, Vols. 301-303, pp. 245-250, 2011
Online since
July 2011
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Price
$32.00
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