Adaptive Synchronization of the Stochastic Delayed RDNNs with Unknown Time-Varying Parameters
Author Name: Weiyuan Zhang
This paper presents a new adaptive synchronization problem for 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.
Date of published: 2013-09-27
Journal Name: Advances In Difference Equations
DOI: Not Available
Keywords: Advances In Difference Equations
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