Global attractivity in delayed Cohen-Grossberg neural network models

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题名:	Global attractivity in delayed Cohen-Grossberg neural network models
作者:	Li,CH;Yang,SY
贡献者:	數學研究所
关键词:	EXPONENTIAL STABILITY;ASYMPTOTIC STABILITY;HARMLESS DELAYS;DISTRIBUTED DELAYS;PERIODIC-SOLUTIONS;CRITERIA
日期:	2009
上传时间:	2010-06-29 19:38:39 (UTC+8)
出版者:	中央大學
摘要:	In this paper, we investigate the global attractivity of Cohen-Grossberg neural network models with connection time delays for both discrete and distributed cases via the Lyapunov functional method. Without assuming the monotonicity and differentiability of activation functions and the symmetry of connection matrix, we establish three new sufficient conditions for the global exponential stability of a unique equilibrium for the delayed Cohen-Grossberg neural network no matter whether the connection time delay is of discrete type or distributed type. In particular, all the three new criteria are independent of time delays and do not include one another. To demonstrate the differences and features of the new stability criteria, several examples are discussed to compare the present results with the existing ones. (C) 2007 Elsevier Ltd. All rights reserved.
關聯:	CHAOS SOLITONS & FRACTALS
显示于类别:	[數學研究所] 期刊論文

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