Adaptive synchronization of delayed reaction-diffusion neural networks with unknown non-identical time-varying coupling strengths

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• 作者：Junmin Li^a ; ^{jmli@mail.xidian.edu.cn}Author Vitae ; Chao He^aAuthor Vitae ; Weiyuan Zhang^bAuthor Vitae ; Minglai Chen^a ; ^cAuthor Vitae
• 关键词：Nonidentical time-varying coupling strengths ; Adaptive ; Reaction-diffusion neural networks (RDNNs) ; Asymptotic synchronization ; Lyapunov-Krasovskii-like composite energy functional (CEF)
• 刊名：Neurocomputing
• 出版年：2017
• 出版时间：5 January 2017
• 年：2017
• 卷：219
• 期：Complete
• 页码：144-153
• 全文大小：2601 K
• 卷排序：219

文摘

This paper concerns the asymptotic synchronization of delayed reaction-diffusion neural networks (RDNNs) with unknown nonidentical time-varying coupling strengths, where the time-varying coupling strengths are consist of continuous time-varying periodic parameters and time-invariant nonnegative parameters. By utilizing a novel adaptive approach, the differential-difference type adaptive laws of coupling strengths and adaptive controller are designed such that the nonidentical RDNNs are asymptotic synchronization. The sufficient conditions dependent on the reaction-diffusion terms are derived by constructing a novel Lyapunov-Krasovskii-like composite energy functional (CEF) and using Barbalat's lemma. Finally, a simulation example is provided to illustrate the effectiveness of the developed approach.