Global asymptotic stability of Cohen-Grossberg neural networks with multiple discrete delays

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	Global asymptotic stability of Cohen-Grossberg neural networks with multiple discrete delays
	Wan, Anhua; Mao, Weihua; Qiao, Hong; Zhang, Bo
	2007
会议名称	3rd International Conference on Intelligent Computing
会议录名称	ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS, PROCEEDINGS: WITH ASPECTS OF ARTIFICIAL INTELLIGENCE
会议日期	AUG 21-24, 2007
会议地点	Qingdao, PEOPLES R CHINA
摘要	The 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.
关键词	Time-varying Delays Exponential Stability Criteria Memory
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12822
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Mao, Weihua
作者单位	S China Agr Univ, Coll Sci, Dept Appl Math
推荐引用方式 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.