Nonlinear measures: A new approach to exponential stability analysis for Hopfield-type neural networks
Qiao, H; Peng, J; Xu, ZB
Source PublicationIEEE TRANSACTIONS ON NEURAL NETWORKS
2001-03
Volume12Issue:2Pages:360-370
AbstractIn 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.
KeywordGlobal Exponential Stability Hopfield-type Neural Networks Local Exponential Stability Matrix Measure Nonlinear Measures
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12583
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Corresponding AuthorQiao, H
AffiliationCity Univ Hong Kong, Dept Mfg Engn & Engn Management
Recommended Citation
GB/T 7714
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.
APA 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.
MLA 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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