Computer Science > Information Theory
This paper has been withdrawn by Yipeng Liu Dr.
[Submitted on 23 Nov 2013 (v1), last revised 7 Feb 2014 (this version, v2)]
Title:Robust Cosparse Greedy Signal Reconstruction for Compressive Sensing with Multiplicative and Additive Noise
No PDF available, click to view other formatsAbstract:Greedy algorithms are popular in compressive sensing for their high computational efficiency. But the performance of current greedy algorithms can be degenerated seriously by noise (both multiplicative noise and additive noise). A robust version of greedy cosparse greedy algorithm (greedy analysis pursuit) is presented in this paper. Comparing with previous methods, The proposed robust greedy analysis pursuit algorithm is based on an optimization model which allows both multiplicative noise and additive noise in the data fitting constraint. Besides, a new stopping criterion that is derived. The new algorithm is applied to compressive sensing of ECG signals. Numerical experiments based on real-life ECG signals demonstrate the performance improvement of the proposed greedy algorithms.
Submission history
From: Yipeng Liu Dr. [view email][v1] Sat, 23 Nov 2013 11:29:06 UTC (125 KB)
[v2] Fri, 7 Feb 2014 10:41:29 UTC (1 KB) (withdrawn)
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