A one-layer recurrent neural network for non-smooth convex optimization subject to linear equality constraints

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5507 LNCS, Issue PART 2, 2009, Pages 1003-1010

  Liu, Qingshan ^a   Wang, Jun ^b  

^a SOUTHEAST UNIVERSITY   (China)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

CONVEX OPTIMIZATION PROBLEMS; DECISION VARIABLES; GLOBAL CONVERGENCE; LINEAR EQUALITY CONSTRAINTS; NON-SMOOTH; OBJECTIVE FUNCTIONS; OPTIMAL SOLUTIONS; OPTIMIZATION PROBLEMS; SIMULATION RESULT; STATE TRAJECTORY;

COMPUTER SIMULATION; DATA PROCESSING; LINEARIZATION; OPTIMIZATION; QUADRATIC PROGRAMMING; RECURRENT NEURAL NETWORKS;

CONVEX OPTIMIZATION;

EID: 70349138424     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03040-6_122     Document Type: Conference Paper

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