Global asymptotic stability of Cohen-Grossberg neural networks with multiple discrete delays
Wan, Anhua; Mao, Weihua; Qiao, Hong; Zhang, Bo
2007
Conference Name3rd International Conference on Intelligent Computing
Source PublicationADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE
Conference DateAUG 21-24, 2007
Conference PlaceQingdao, PEOPLES R CHINA
AbstractThe asymptotic stability is analyzed for Cohen-Grossberg neural networks with multiple discrete delays. The boundedness, differentiability or monotonicity condition is not assumed on the activation functions. The generalized Dahlquist constant approach is employed to examine the existence and uniqueness of equilibrium of the neural networks, and a novel Lyapunov functional is constructed to investigate the stability of the delayed neural networks. New general sufficient conditions are derived for the global asymptotic stability of the neural networks with multiple delays.
KeywordTime-varying Delays Exponential Stability Criteria Memory
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12822
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 AuthorMao, Weihua
AffiliationS China Agr Univ, Coll Sci, Dept Appl Math
Recommended Citation
GB/T 7714
Wan, Anhua,Mao, Weihua,Qiao, Hong,et al. Global asymptotic stability of Cohen-Grossberg neural networks with multiple discrete delays[C],2007.
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