Proceedings of the 2014 International Conference on Computer, Communications and Information Technology

Augmented l1 Minimization with Weibull Matrix

Authors
Tailong Li, Qihao Zhang
Corresponding Author
Tailong Li
Available Online January 2014.
DOI
https://doi.org/10.2991/ccit-14.2014.8How to use a DOI?
Keywords
Compressed sensing, sparsity, robust null space property, Weibull random variable, linearized Bregman iteration
Abstract
The linearized Bregman iteration was successful used to find the sparse signal from the its noise measurements. It was proved that the iteration algorithm converges to the augmented l1 minimization problem [4]. This paper mainly considers the measurement matrix A which is generated by the Weibull random distribution. With the optimal number of the measurements, the stability of the augmented l1 minimization model is given.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Intelligent Systems Research
Publication Date
January 2014
ISBN
978-90786-77-97-0
ISSN
1951-6851
DOI
https://doi.org/10.2991/ccit-14.2014.8How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Tailong Li
AU  - Qihao Zhang
PY  - 2014/01
DA  - 2014/01
TI  - Augmented l1 Minimization with Weibull Matrix
PB  - Atlantis Press
SP  - 26
EP  - 28
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.8
DO  - https://doi.org/10.2991/ccit-14.2014.8
ID  - Li2014/01
ER  -