Augmented l1 Minimization with Weibull Matrix
- 10.2991/ccit-14.2014.8How to use a DOI?
- Compressed sensing, sparsity, robust null space property, Weibull random variable, linearized Bregman iteration
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 . 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.
- © 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/).
Cite this article
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 -