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58832 |
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|a Berinde, Radu
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Indyk, Piotr
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|a Indyk, Piotr
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|a Berinde, Radu
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|a Indyk, Piotr
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|a Sequential sparse matching pursuit
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|b Institute of Electrical and Electronics Engineers,
|c 2010-10-01T18:19:38Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/58832
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|a We propose a new algorithm, called sequential sparse matching pursuit (SSMP), for solving sparse recovery problems. The algorithm provably recovers a k-sparse approximation to an arbitrary n-dimensional signal vector x from only O(k log(n/k)) linear measurements of x. The recovery process takes time that is only near-linear in n. Preliminary experiments indicate that the algorithm works well on synthetic and image data, with the recovery quality often outperforming that of more complex algorithms, such as à ¿1 minimization.
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|a en_US
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|a Article
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|t Allerton Conference on Communication, Control, and Computing
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