Synchronization of delayed reaction-diffusion neural networks via an adaptive learning control approach

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• 作者：Junmin Li^a ; ^{jmli@mail.xidian.edu.cn} ; Weiyuan Zhang^a ; ^b ; Minglai Chen^a
• 关键词：Synchronization ; Reaction&ndash ; diffusion neural networks ; Unknown time-varying coupling strengths ; Adaptive learning laws ; Delay
• 刊名：Computers and Mathematics with Applications
• 出版年：2013
• 出版时间：July, 2013
• 年：2013
• 卷：65
• 期：11
• 页码：1775-1785
• 全文大小：1071 K

文摘

An adaptive learning control strategy is utilized to investigate the synchronization problem for delayed reaction-diffusion neural networks (RDNNs) with unknown time-varying coupling strengths. A novel adaptive synchronization approach is proposed, which is consisted of differential-difference type updating law and feedback control law. By constructing a Lyapunov-Krasovskii-like composite energy functional (CEF), based on the LaSalle invariant principle of functional differential equations, a sufficient condition for the adaptive synchronization of such a system is obtained. Finally, a numerical example is given to show the effectiveness of the proposed synchronization method.