Expectation maximization based matching pursuit
buir.contributor.author | Arıkan, Orhan | |
buir.contributor.orcid | Arıkan, Orhan|0000-0002-3698-8888 | |
dc.citation.epage | 3316 | en_US |
dc.citation.spage | 3313 | en_US |
dc.contributor.author | Gurbuz, A.C. | en_US |
dc.contributor.author | Pilanci, M. | en_US |
dc.contributor.author | Arıkan, Orhan | en_US |
dc.coverage.spatial | Kyoto, Japan | en_US |
dc.date.accessioned | 2016-02-08T12:12:33Z | |
dc.date.available | 2016-02-08T12:12:33Z | |
dc.date.issued | 2012 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description | Date of Conference: 25-30 March 2012 | en_US |
dc.description.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. | en_US |
dc.description.provenance | Made available in DSpace on 2016-02-08T12:12:33Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2012 | en |
dc.identifier.doi | 10.1109/ICASSP.2012.6288624 | en_US |
dc.identifier.issn | 1520-6149 | |
dc.identifier.uri | http://hdl.handle.net/11693/28153 | |
dc.language.iso | English | en_US |
dc.publisher | IEEE | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1109/ICASSP.2012.6288624 | en_US |
dc.source.title | 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) | en_US |
dc.subject | Compressive sensing | en_US |
dc.subject | Expectation Maximization | en_US |
dc.subject | Greedy algorithms | en_US |
dc.subject | Greedy method | en_US |
dc.subject | Incomplete data | en_US |
dc.subject | Matching pursuit | en_US |
dc.subject | Orthogonal matching pursuit | en_US |
dc.subject | Reconstruction error | en_US |
dc.subject | Sparse reconstruction | en_US |
dc.subject | Sparse solutions | en_US |
dc.subject | Channel estimation | en_US |
dc.subject | Iterative methods | en_US |
dc.subject | Maximum principle | en_US |
dc.subject | Signal processing | en_US |
dc.subject | Algorithms | en_US |
dc.title | Expectation maximization based matching pursuit | en_US |
dc.type | Conference Paper | en_US |
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