Global exponential stability of a class of memristor-based recurrent neural networks with time-varying delays

Neurocomputing

Volumn 97, Issue , 2012, Pages 149-154

  Zhang, Guodong ^a,b,c   Shen, Yi ^a,b   Sun, Junwei ^a,b  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^c HUBEI NORMAL UNIVERSITY   (China)

Author keywords

Global exponential stability; Memristor; Recurrent neural networks; Time varying delays

Indexed keywords

ACTIVATION FUNCTIONS; CONNECTION WEIGHTS; DELAY FUNCTION; GLOBAL EXPONENTIAL STABILITY; MEMRISTOR; RIGHT-HAND SIDES; TIME-VARYING DELAY;

DIFFERENTIAL EQUATIONS; MEMRISTORS; PASSIVE FILTERS; RECURRENT NEURAL NETWORKS; RESISTORS; TIME VARYING CONTROL SYSTEMS;

TIME VARYING NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION ALGORITHM; COMPUTER SIMULATION; GLOBAL EXPONENTIAL STABILITY; LINEAR SYSTEM; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PRIORITY JOURNAL; SIGNAL PROCESSING; STATISTICAL SIGNIFICANCE; SYSTEM ANALYSIS; SYSTEMS THEORY; TIME SERIES ANALYSIS;

EID: 84865314918     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.05.002     Document Type: Article

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