DocumentCode :
2544485
Title :
A Compressed Sensing reconstruct algorithm based on trust region method of nonsmooth optimization
Author :
Dong Enming ; Li Jianping ; Liu Jinjie
Author_Institution :
Coll. of Sci., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
1655
Lastpage :
1658
Abstract :
The signal reconstruction problems of Compressed Sensing is equal to a nonsmooth optimization problem. Since the original signal is sparse, a new l1 -Minimization reconstruction algorithm is proposed based on modified trust region method of nonsmooth optimization. The algorithm can also reconstruct signal in super-linear convergence rate. Simulation results show that the algorithm is robust in reconstructing the original signal.
Keywords :
optimisation; signal reconstruction; compressed sensing reconstruct algorithm; minimization reconstruction algorithm; modified trust region method; nonsmooth optimization problem; signal reconstruction problems; trust region method; Compressed sensing; Convergence; Image reconstruction; Optimization; Signal processing algorithms; Signal reconstruction; Transforms; compressed sensing; modified trust region method; nonsmooth optimization; reconstruction algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6233910
Filename :
6233910
Link To Document :
بازگشت