Complete Delay-Decomposing Approach to Asymptotic Stability for Neural Networks With Time-Varying Delays

This paper is concerned with the problem of stability of neural networks with time-varying delays. A novel Lyapunov-Krasovskii functional decomposing the delays in all integral terms is proposed. By exploiting all possible information and considering independent upper bounds of the delay derivative...

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Veröffentlicht in:	IEEE transactions on neural networks 2011-05, Vol.22 (5), p.806-812
Hauptverfasser:	Zeng, Hong-Bing, He, Yong, Wu, Min, Zhang, Chang-Fan
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Artificial Intelligence Artificial neural networks Asymptotic stability Computer science control theory systems Connectionism. Neural networks Delay Delay-dependent Exact sciences and technology neural networks Neural Networks (Computer) Reaction Time stability Stability criteria Symmetric matrices Time Factors time-varying delay Upper bound
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