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Conjugate Gradient Iterative Hard Thresholding: Observed Noise Stability for Compressed Sensing

Abstract:
Conjugate Gradient Iterative Hard Thresholding (CGIHT) for compressed sensing combines the low per iteration complexity of fast greedy sparse approximation algorithms with the improved convergence rates of more complicated, projection based algorithms. This article shows that CGIHT is robust to additive noise and is typically the fastest greedy algorithm in the presence of noise.

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Publisher:
IEEE International Symposium on Information Theory
Publication date:
2014-01-01
UUID:
uuid:21ce4fbf-cbbb-45b4-8b50-49f5999914ed
Local pid:
oai:eprints.maths.ox.ac.uk:1806
Deposit date:
2014-02-28

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