DocumentCode :
3575975
Title :
Synthesis-based sparse reconstrucion with analysis-based solvers
Author :
Di Wu ; Yuxin Zhao ; Shuai Chang ; Kaiyu Wang
Author_Institution :
Coll. of Autom., Harbin Eng. Univ., Harbin, China
fYear :
2014
Firstpage :
1257
Lastpage :
1260
Abstract :
Synthesis sparsity model received great attention in the past decade. Signal reconstruction based analysis model appears recently and has a high accurate reconstruction rate., which constitutes a solid basis for practical applications. In this paper, we transform the sparse signal reconstruction issue of synthesis model to an analysis one with some additional restraints. Therefore the existing algorithms based on analysis model are able to solve the exact reconstruction problem of synthesis model. This approach is called the Synthesis-By-Analysis(SBA) approach. The proposed approach is evaluated by comparing it with the Orthogonal Matching Pursuit algorithm, which is a classic algorithm base on the synthesis model. Experiment results show that this approach is another option for reconstruction problem based on synthesis model, meanwhile allowing many algorithms for analysis cosparse model to be used for synthesis signal reconstruction as well.
Keywords :
iterative methods; signal reconstruction; signal synthesis; SBA approach; analysis-based solvers; orthogonal matching pursuit algorithm; reconstruction rate; signal reconstruction based analysis model; sparse signal reconstruction; synthesis sparsity model; synthesis-based sparse reconstruction; synthesis-by-analysis approach; Algorithm design and analysis; Analytical models; Dictionaries; Matching pursuit algorithms; Mathematical model; Signal processing algorithms; Signal reconstruction; Analysis cosparse model; sparse reconstruction; synthesis by analysis; synthesis sparse model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Control (ICMC), 2014 International Conference on
Print_ISBN :
978-1-4799-2537-7
Type :
conf
DOI :
10.1109/ICMC.2014.7231754
Filename :
7231754
Link To Document :
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