Exponential stability of impulsive high-order Hopfield-type neural networks with time-varying delays

IEEE Transactions on Neural Networks

Volumn 16, Issue 6, 2005, Pages 1329-1339

  Liu, Xinzhi ^a   Teo, Kok Lay ^b   Xu, Bingji ^c  

^a UNIVERSITY OF WATERLOO   (Canada)

^b CURTIN UNIVERSITY   (Australia)

^c HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Exponential stability; Impulsive high order Hopfield type Lyapunov function; Neural networks

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; LYAPUNOV METHODS; MATHEMATICAL MODELS; STABILITY CRITERIA; SYSTEM STABILITY;

EXPONENTIAL STABILITY; IMPULSIVE HIGH ORDER HOPFIELD LYAPUNOV FUNCTION; TIME VARYING DELAY;

NEURAL NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; NONLINEAR SYSTEM; SIGNAL PROCESSING; STATISTICAL MODEL; TIME;

ALGORITHMS; COMPUTER SIMULATION; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; SIGNAL PROCESSING, COMPUTER-ASSISTED; TIME FACTORS;

EID: 28244432161     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2005.857949     Document Type: Article

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