A fast decoder for compressed sensing based multiple description image coding
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Efficient optimization of an MDL-inspired objective function for unsupervised part-of-speech tagging
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
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ℓ0 norm based signal recovery is attractive in compressed sensing as it can facilitate exact recovery of sparse signal with very high probability. Unfortunately, direct ℓ0 norm minimization problem is NP-hard. This paper describes an approximate ℓ0 norm algorithm for sparse representation which preserves most of the advantages of ℓ0 norm. The algorithm shows attractive convergence properties, and provides remarkable performance improvement in noisy environment compared to other popular algorithms. The sparse representation algorithm presented is capable of very fast signal recovery, thereby reducing retrieval latency when handling