Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing

Heng Li Pei; Tao Shang; Jian Wei Liu

doi:10.1109/ICADE.2012.6330117

Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing

Heng Li Pei^*
, Tao Shang
, Jian Wei Liu

^*Corresponding author for this work

School of Cyber Science and Technology

Beihang University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Standard CS (Compressive Sensing) indicates the number of the samples which should be taken from the original signal in the sender to be reconstructed in the receiver is M ≥ CKμ log N. In the inequality, all of the variables can be known except for C. This paper mainly discusses the factors that influence this variable. Our contributions can be concluded into two aspects: firstly, we conclude that the length N and the sparsity K of the original signal are not the main factors that influence C and it is influenced by the type of measurement matrix and reconstruction algorithm; secondly, we provide the lower bound of C which can be used in practice to reconstruct the original signal with high precision.

Original language	English
Title of host publication	Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012
Pages	149-153
Number of pages	5
DOIs	https://doi.org/10.1109/ICADE.2012.6330117
State	Published - 2012
Event	2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012 - Beijing, China Duration: 27 Jul 2012 → 29 Jul 2012

Publication series

Name	Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012

Conference

Conference	2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012
Country/Territory	China
City	Beijing
Period	27/07/12 → 29/07/12

Keywords

Gaussian matrix
OMP
RIP
compressive sensing

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10.1109/ICADE.2012.6330117

Cite this

Pei, H. L., Shang, T., & Liu, J. W. (2012). Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing. In Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012 (pp. 149-153). Article 6330117 (Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012). https://doi.org/10.1109/ICADE.2012.6330117

Pei, Heng Li ; Shang, Tao ; Liu, Jian Wei. / Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing. Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012. 2012. pp. 149-153 (Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012).

@inproceedings{60473c994b894fb6b8590c48997580f5,

title = "Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing",

abstract = "Standard CS (Compressive Sensing) indicates the number of the samples which should be taken from the original signal in the sender to be reconstructed in the receiver is M ≥ CKμ log N. In the inequality, all of the variables can be known except for C. This paper mainly discusses the factors that influence this variable. Our contributions can be concluded into two aspects: firstly, we conclude that the length N and the sparsity K of the original signal are not the main factors that influence C and it is influenced by the type of measurement matrix and reconstruction algorithm; secondly, we provide the lower bound of C which can be used in practice to reconstruct the original signal with high precision.",

keywords = "Gaussian matrix, OMP, RIP, compressive sensing",

author = "Pei, \{Heng Li\} and Tao Shang and Liu, \{Jian Wei\}",

year = "2012",

doi = "10.1109/ICADE.2012.6330117",

language = "英语",

isbn = "9781467313322",

series = "Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012",

pages = "149--153",

booktitle = "Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012",

note = "2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012 ; Conference date: 27-07-2012 Through 29-07-2012",

}

Pei, HL, Shang, T & Liu, JW 2012, Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing. in Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012., 6330117, Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012, pp. 149-153, 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012, Beijing, China, 27/07/12. https://doi.org/10.1109/ICADE.2012.6330117

Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing. / Pei, Heng Li; Shang, Tao ; Liu, Jian Wei.
Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012. 2012. p. 149-153 6330117 (Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing

AU - Pei, Heng Li

AU - Shang, Tao

AU - Liu, Jian Wei

PY - 2012

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N2 - Standard CS (Compressive Sensing) indicates the number of the samples which should be taken from the original signal in the sender to be reconstructed in the receiver is M ≥ CKμ log N. In the inequality, all of the variables can be known except for C. This paper mainly discusses the factors that influence this variable. Our contributions can be concluded into two aspects: firstly, we conclude that the length N and the sparsity K of the original signal are not the main factors that influence C and it is influenced by the type of measurement matrix and reconstruction algorithm; secondly, we provide the lower bound of C which can be used in practice to reconstruct the original signal with high precision.

AB - Standard CS (Compressive Sensing) indicates the number of the samples which should be taken from the original signal in the sender to be reconstructed in the receiver is M ≥ CKμ log N. In the inequality, all of the variables can be known except for C. This paper mainly discusses the factors that influence this variable. Our contributions can be concluded into two aspects: firstly, we conclude that the length N and the sparsity K of the original signal are not the main factors that influence C and it is influenced by the type of measurement matrix and reconstruction algorithm; secondly, we provide the lower bound of C which can be used in practice to reconstruct the original signal with high precision.

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KW - compressive sensing

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BT - Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012

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Pei HL, Shang T , Liu JW. Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing. In Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012. 2012. p. 149-153. 6330117. (Proceedings - 2012 IEEE International Conference on Intelligent Control, Automatic Detection and High-End Equipment, ICADE 2012). doi: 10.1109/ICADE.2012.6330117

Empirical analysis of the C-value in the conditional inequality of dimension of measurement matrix in compressive sensing

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