Sparse approximations with a high resolution greedy algorithm

Benjamin G. Salomon, Hanoch Ur

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Signal decomposition with an overcomplete dictionary is nonunique. Computation of the best approximation is known to be NP-hard problem. The matching pursuit (MP) algorithm is a popular iterative greedy algorithm that finds a sub-optimal approximation, by picking at each iteration the vector that best correlates with the present residual. Choosing approximation vectors by optimizing a correlation inner product can produce a loss of time and frequency resolution. We propose a modified MP, based on a post processing step applied on the resulting MP approximation, using backward greedy algorithm, to achieve higher resolution than the original MP.

Original languageEnglish
Title of host publication11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004
Pages330-333
Number of pages4
StatePublished - 2004
Event11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004 - Tel Aviv, Israel
Duration: 13 Dec 200415 Dec 2004

Publication series

Name11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004

Conference

Conference11th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2004
Country/TerritoryIsrael
CityTel Aviv
Period13/12/0415/12/04

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