Sufficient and necessary conditions for global exponential stability of discrete-time recurrent neural networks

IEEE Transactions on Circuits and Systems I: Regular Papers

Volumn 53, Issue 6, 2006, Pages 1373-1380

  Wang, Lisheng ^a,b   Xu, Zongben ^b  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

^b XI'AN JIAOTONG UNIVERSITY   (China)

Author keywords

Discrete time recurrent neural networks; Exponential bound; Global asymptotic stability (GAS); Global exponential stability (GES); Nonlinear difference equations

Indexed keywords

ASYMPTOTIC STABILITY; CONVERGENCE OF NUMERICAL METHODS; MATRIX ALGEBRA; NONLINEAR EQUATIONS; RECURRENT NEURAL NETWORKS;

DISCRETE-TIME RECURRENT NEURAL NETWORKS; EXPONENTIAL BOUND; GLOBAL ASYMPTOTIC STABILITY (GAS); GLOBAL EXPONENTIAL STABILITY (GES); JACOBIAN MATRIX; NONLINEAR DIFFERENCE EQUATIONS;

DISCRETE TIME CONTROL SYSTEMS;

EID: 33747143187     PISSN: 10577122     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCSI.2006.874179     Document Type: Article

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