|Nonlinear measures: A new approach to exponential stability analysis for Hopfield-type neural networks|
|Qiao, H; Peng, J; Xu, ZB
|Source Publication||IEEE TRANSACTIONS ON NEURAL NETWORKS
|Abstract||In this paper, a new concept called nonlinear measure is introduced to quantify stability of nonlinear systems in the way similar to the matrix measure for stability of linear systems. Based on the new concept, a novel approach for stability analysis of neural networks is developed. With this approach, a series of new sufficient conditions for global and focal exponential stability of Hopfield type neural networks is presented, which generalizes those existing results. By means of the introduced nonlinear measure, the exponential convergence rate of the neural networks to stable equilibrium point is estimated, and, for local stability, the attraction region of the stable equilibrium point is characterized. The developed approach tan be generalized to stability analysis of other general nonlinear systems.|
|Keyword||Global Exponential Stability
Hopfield-type Neural Networks
Local Exponential Stability
|Corresponding Author||Qiao, H|
|Affiliation||City Univ Hong Kong, Dept Mfg Engn & Engn Management|
Qiao, H,Peng, J,Xu, ZB. Nonlinear measures: A new approach to exponential stability analysis for Hopfield-type neural networks[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS,2001,12(2):360-370.
Qiao, H,Peng, J,&Xu, ZB.(2001).Nonlinear measures: A new approach to exponential stability analysis for Hopfield-type neural networks.IEEE TRANSACTIONS ON NEURAL NETWORKS,12(2),360-370.
Qiao, H,et al."Nonlinear measures: A new approach to exponential stability analysis for Hopfield-type neural networks".IEEE TRANSACTIONS ON NEURAL NETWORKS 12.2(2001):360-370.
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