IEEE Trans Cybern. 2019 Feb;49(2):712-718. doi: 10.1109/TCYB.2017.2765343. Epub 2017 Oct 30.
We study the problem of master-slave synchronization of two delayed memristive neural networks (MNNs). Different from most previous papers, memristors are regarded as uncertain continuous time-varying parameters, and MNNs are modeled by neural networks (NNs) with continuous time-varying parameters and polytopic uncertainty. Thus, synchronization of two delayed MNNs is converted into synchronization of delayed NNs with uncertain parameter mismatches. Quasi-synchronization criteria are derived by Lyapunov function and inequality technique. It is shown that, given a predetermined error bound, quasi-synchronization of two delayed chaotic MNNs can be achieved provided that the pinning strength is larger than a threshold. In the end, a numerical example is provided to illustrate the effectiveness of the derived results.
我们研究了两个时滞忆阻神经网络（MNN）的主从同步问题。与大多数先前的论文不同，我们将忆阻器视为不确定的时变连续参数，并且将 MNN 建模为具有时变连续参数和多面体不确定性的神经网络（NN）。因此，两个时滞 MNN 的同步被转化为具有不确定参数失配的时滞 NN 的同步。通过 Lyapunov 函数和不等式技术推导出准同步准则。结果表明，在给定预定误差边界的情况下，只要钉扎强度大于阈值，就可以实现两个时滞混沌 MNN 的准同步。最后，提供了一个数值实例来说明所得到的结果的有效性。
