Augmented l1 Minimization with Weibull Matrix

DOI

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.

Copyright

© 2014, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Tailong Li
AU  - Qihao Zhang
PY  - 2014/01
DA  - 2014/01
TI  - Augmented l1 Minimization with Weibull Matrix
BT  - Proceedings of the 2014 International Conference on Computer, Communications and Information Technology
PB  - Atlantis Press
SP  - 26
EP  - 28
SN  - 1951-6851
UR  - https://doi.org/10.2991/ccit-14.2014.8
DO  - 10.2991/ccit-14.2014.8
ID  - Li2014/01
ER  -