A neurodynamic optimization method for recovery of compressive sensed signals with globally converged solution approximating to l0 Minimization

IEEE Transactions on Neural Networks and Learning Systems

Volumn 26, Issue 7, 2015, Pages 1363-1374

  Guo, Chengan ^a   Yang, Qingshan ^a,b  

^a DALIAN UNIVERSITY OF TECHNOLOGY   (China)

^b CHINA ELECTRONICS TECHNOLOGY GROUP CORPORATION   (China)

Author keywords

Adaptive parameter adjustment; compressive sensing; l norm minimization; modified Gaussian function; neurodynamic optimization; recovery of sparse signals

Indexed keywords

ALGORITHMS; COMPRESSED SENSING; COMPUTATIONAL COMPLEXITY; OPTIMAL SYSTEMS; ORTHOGONAL FUNCTIONS; RECOVERY; RECURRENT NEURAL NETWORKS;

ADAPTIVE PARAMETER ADJUSTMENT; COMPRESSIVE SENSING; GAUSSIAN FUNCTIONS; NEURODYNAMIC OPTIMIZATIONS; SPARSE SIGNALS;

OPTIMIZATION;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; IMAGE PROCESSING; INFORMATION PROCESSING; NORMAL DISTRIBUTION; PROCEDURES; SIGNAL PROCESSING; STATISTICAL MODEL;

ALGORITHMS; DATA COMPRESSION; IMAGE PROCESSING, COMPUTER-ASSISTED; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NORMAL DISTRIBUTION; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 84933043170     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2014.2341654     Document Type: Article

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