A recurrent neural network for solving a class of general variational inequalities

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

Volumn 37, Issue 3, 2007, Pages 528-539

  Hu, Xiaolin ^a   Wang, Jun ^a  

^a CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

Author keywords

General projection neural network (GPNN); General variational inequalities (GVIs); Global asymptotic stability; Global exponential stability; Recurrent neural network

Indexed keywords

ASYMPTOTIC STABILITY; CONVERGENCE OF NUMERICAL METHODS; VARIATIONAL TECHNIQUES;

GENERAL PROJECTION NEURAL NETWORK; GENERAL VARIATIONAL INEQUALITIES;

RECURRENT NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; DECISION SUPPORT SYSTEM; FEEDBACK SYSTEM; MATHEMATICAL COMPUTING; THEORETICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; DECISION SUPPORT TECHNIQUES; FEEDBACK; MATHEMATICAL COMPUTING; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); NUMERICAL ANALYSIS, COMPUTER-ASSISTED;

EID: 34249007164     PISSN: 10834419     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSMCB.2006.886166     Document Type: Article

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