A New Performance Measure Using $k$ -Set Correlation for Compressed Sensing Matrices

Author

Hong, Seokbeom ; Park, Hosung ; Shin, Beomkyu ; No, Jong-Seon ; Chung, Habong

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ., Seoul, South Korea

Volume

19

Issue

3

fYear

2012

fDate

3/1/2012 12:00:00 AM

Firstpage

143

Lastpage

146

Abstract

In this letter, a new performance measure for compressed sensing matrices is proposed. This new measure is based on the k-set correlation vectors whose components consist of the correlation values between two columns in the k-column submatrices of a sensing matrix. This measure is highly related to the restricted isometry property (RIP). And the proposed measure has less computational complexity than the condition number approach which is a typical approach for performance prediction with RIP check. It is shown by simulation that the proposed scheme works well as a performance measure for the compressed sensing matrices.

Keywords

computational complexity; correlation theory; data compression; matrix algebra; signal reconstruction; compressed sensing matrices; computational complexity; k-column submatrices; k-set correlation vectors; restricted isometry property; Approximation methods; Coherence; Compressed sensing; Correlation; Educational institutions; Sensors; Vectors; $k$ -set correlation; Coherence; compressed sensing; restricted isometry property (RIP); sequences;

fLanguage

English

Journal_Title

Signal Processing Letters, IEEE

Publisher

ieee

ISSN

1070-9908

Type

jour

DOI

10.1109/LSP.2012.2183365

Filename

6125989

A New Performance Measure Using -Set Correlation for Compressed Sensing Matrices

Hong, Seokbeom ; Park, Hosung ; Shin, Beomkyu ; No, Jong-Seon ; Chung, Habong

jour

A New Performance Measure Using $k$ -Set Correlation for Compressed Sensing Matrices