Adaptive synchronization of the stochastic delayed RDNNs with unknown time-varying parameters

Advances in Difference Equations

Junmin Li¹  Weiyuan Zhang²  Minglai Chen³ 

[1] Department of Mathematics, Xidian University, ShaanXi, Xi’Institute of Mathematics and Applied Mathematics, Xianyang Normal University, ShaanXi, Xianyang, China;an, China

关键词: reaction-diffusion neural networks;    unknown time-varying coupling strengths;    stochastic synchronization;    adaptive learning control;    delay;   

DOI  :  10.1186/1687-1847-2013-253

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

This paper presents a new adaptive synchronization problem for the delayed reaction-diffusion neural networks (RDNNs) with unknown time-varying coupling strengths under stochastic perturbations. By constructing a differential-difference-type learning law and an adaptive learning control law, and using Lyapunov-Krasovskii-like composite energy functional method, a novel sufficient condition is derived to ensure adaptive asymptotical synchronization in the mean square sense for the addressed system. Finally, a numerical example is given to verify the effectiveness of the proposed method.

【 授权许可】

CC BY