Robust stability analysis of interval fuzzy Cohen-Grossberg neural networks with piecewise constant argument of generalized type

Neural Networks

Volumn 33, Issue , 2012, Pages 32-41

  Bao, Gang ^a,b   Wen, Shiping ^a,b   Zeng, Zhigang ^a,b  

^a HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Fuzzy recurrent neural networks; Global robustly exponential stability; Piecewise constant argument

Indexed keywords

COHEN-GROSSBERG NETWORKS; COHEN-GROSSBERG NEURAL NETWORKS; COMPARISON PRINCIPLE; EXISTENCE AND UNIQUENESS; GLOBAL ROBUST EXPONENTIAL STABILITIES; PIECEWISE CONSTANT ARGUMENT; ROBUST STABILITY ANALYSIS; THEORETICAL RESULT;

RECURRENT NEURAL NETWORKS; SYSTEM STABILITY;

ROBUSTNESS (CONTROL SYSTEMS);

ARTICLE; ARTIFICIAL NEURAL NETWORK; INTERVAL FUZZY COHEN GROSSBERG NEURAL NETWORK; MATHEMATICAL MODEL; PRIORITY JOURNAL; THEORETICAL STUDY;

FUZZY LOGIC; NEURAL NETWORKS (COMPUTER); REPRODUCIBILITY OF RESULTS; TIME FACTORS;

EID: 84863875125     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2012.04.003     Document Type: Article

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