New algebraic conditions for global exponential stability of delayed recurrent neural networks

Neurocomputing

Volumn 64, Issue 1-4 SPEC. ISS., 2005, Pages 319-333

  Li, Chuandong ^a   Liao, Xiaofeng ^a  

^a CHONGQING UNIVERSITY   (China)

Author keywords

Bi directional associative memory neural networks; Delayed recurrent neural networks; Global exponential stability; Lyapunov functional

Indexed keywords

ASYMPTOTIC STABILITY; FUNCTIONS; LINEAR ALGEBRA; LYAPUNOV METHODS; MATHEMATICAL MODELS;

ACTIVATION FUNCTIONS; ALGEBRAIC CONDITIONS; GLOBAL EXPONENTIAL STABILITY;

RECURRENT NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER MODEL; COMPUTER SIMULATION; CORRELATION COEFFICIENT; HYPOTHESIS; MATHEMATICAL ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NONLINEAR SYSTEM; PRIORITY JOURNAL; SIGNAL DETECTION; STATISTICAL ANALYSIS;

EID: 15844378218     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2004.10.104     Document Type: Article

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