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Home » Adaptive Synchronization of the Stochastic Delayed RDNNs with Unknown Time-Varying Parameters

  1. 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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