Expectation maximization based matching pursuit

Date
2012
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Source Title
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Print ISSN
1520-6149
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Publisher
IEEE
Volume
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Pages
3313 - 3316
Language
English
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Abstract

A novel expectation maximization based matching pursuit (EMMP) algorithm is presented. The method uses the measurements as the incomplete data and obtain the complete data which corresponds to the sparse solution using an iterative EM based framework. In standard greedy methods such as matching pursuit or orthogonal matching pursuit a selected atom can not be changed during the course of the algorithm even if the signal doesn't have a support on that atom. The proposed EMMP algorithm is also flexible in that sense. The results show that the proposed method has lower reconstruction errors compared to other greedy algorithms using the same conditions. © 2012 IEEE.

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Published Version (Please cite this version)