Compressed Sensing Performance of Random Bernoulli Matrices with High Compression Ratio

This letter studies the sensing performance of random Bernoulli matrices with column size n much larger than row size m. It is observed that as the compression ratio n/m increases, this kind of matrices tends to present a performance floor regarding the guaranteed signal sparsity. The performance fl...

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Bibliographic Details
Published inIEEE signal processing letters Vol. 22; no. 8; pp. 1074 - 1078
Main Authors Weizhi Lu, Weiyu Li, Kpalma, Kidiyo, Ronsin, Joseph
Format Journal Article
LanguageEnglish
Published New York IEEE 01.08.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects
Bernoulli distribution
Compressed
Compressed sensing
Compression ratio
Correlation
Detection
Electronic mail
Engineering Sciences
Estimation
high dimension
Materials
Powder injection molding
random matrix
Sensors
Signal and Image processing
Signal processing
Sparse matrices
random matrix
Bernoulli distribution
compressed sensing
high dimension
compression ratio
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Summary:This letter studies the sensing performance of random Bernoulli matrices with column size n much larger than row size m. It is observed that as the compression ratio n/m increases, this kind of matrices tends to present a performance floor regarding the guaranteed signal sparsity. The performance floor is effectively estimated with the formula 1 /2(√{πm/2} + 1). To the best of our knowledge, it is the first time in compressed sensing, a theoretical estimation is successfully proposed to reflect the real performance.
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2014.2385813