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COMPRESSED SENSING SIGNAL RECOVERY VIA A* ORTHOGONAL MATCHING PURSUIT

Full Paper at IEEE Xplore

Compressed Sensing: Theory and Methods

Přednášející: Nazim Burak Karahanoglu, Autoři: Nazim Burak Karahanoglu, TUBITAK - BILGEM, Turkey; Hakan Erdogan, Sabanci University, Turkey

Reconstruction of sparse signals acquired in reduced dimensions requires the solution with minimum l0 norm. As solving the l0 minimization directly is unpractical, a number of algorithms have appeared for finding an indirect solution. A semi-greedy approach, A* Orthogonal Matching Pursuit (A*OMP), is proposed in [1] where the solution is searched on several paths of a search tree. Paths of the tree are evaluated and extended according to some cost function, for which novel dynamic auxiliary cost functions are suggested. This paper describes the A*OMP algorithm and the proposed cost functions briefly. The novel dynamic auxiliary cost functions are shown to provide improved results as compared to a conventional choice. Reconstruction performance is illustrated on both synthetically generated data and real images, which show that the proposed scheme outperforms well-known CS reconstruction methods.


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  Informace o přednášce

Nahráno: 2011-05-26 14:05 - 14:25, Club B
Přidáno: 18. 6. 2011 15:22
Počet zhlédnutí: 85
Rozlišení videa: 1024x576 px, 512x288 px
Délka videa: 0:19:27
Audio stopa: MP3 [6.57 MB], 0:19:27