Statistical mechanical analysis of compressed sensing utilizing correlated compression matrix

Author

Takeda, Koujin ; Kabashima, Yoshiyuki

Author_Institution

Dept. of Comput. Intell. & Syst. Sci., Tokyo Inst. of Technol., Yokohama, Japan

fYear

2010

fDate

13-18 June 2010

Firstpage

1538

Lastpage

1542

Abstract

We investigate a reconstruction limit of compressed sensing for a reconstruction scheme based on the L₁-norm minimization utilizing a correlated compression matrix with a statistical mechanics method. We focus on the compression matrix modeled as the Kronecker-type random matrix studied in research on multiple-input multiple-output wireless communication systems. We found that strong one-dimensional correlations between expansion bases of original information slightly degrade reconstruction performance.

Keywords

matrix algebra; signal processing; statistical analysis; Kronecker-type random matrix; L1-norm minimization; compressed sensing; correlated compression matrix; multiple-input multiple-output wireless communication system; one-dimensional correlation; reconstruction performance; reconstruction scheme; statistical mechanical analysis; statistical mechanics method; Compressed sensing; Computational intelligence; Data compression; Degradation; MIMO; Minimization methods; Random variables; Symmetric matrices; Vectors; Wireless communication;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Theory Proceedings (ISIT), 2010 IEEE International Symposium on

Conference_Location

Austin, TX

Print_ISBN

978-1-4244-7890-3

Electronic_ISBN

978-1-4244-7891-0

Type

conf

DOI

10.1109/ISIT.2010.5513523

Filename

5513523