具有时滞和扩散项的忆阻神经网络的全局指数同步。
Global exponential synchronization of delayed memristive neural networks with reaction-diffusion terms.
机构信息
Centre for Artificial Intelligence, University of Technology Sydney, Sydney, 2007, Australia.
College of Mathematics and Econometrics, Hunan University, Changsha, PR China.
出版信息
Neural Netw. 2020 Mar;123:70-81. doi: 10.1016/j.neunet.2019.11.008. Epub 2019 Nov 29.
This paper investigates the global exponential synchronization problem of delayed memristive neural networks (MNNs) with reaction-diffusion terms. First, by utilizing the pinning control technique, two novel kinds of control methods are introduced to achieve synchronization of delayed MNNs with reaction-diffusion terms. Then, with the help of inequality techniques, pinning control technique, the drive-response concept and Lyapunov functional method, two sufficient conditions are obtained in the form of algebraic inequalities, which can be used for ensuring the exponential synchronization of the proposed delayed MNNs with reaction-diffusion terms. Moreover, the obtained results based on algebraic inequality complement and improve the previously known results. Finally, two illustrative examples are given to support the effectiveness and validity of the obtained theoretical results.
本文研究了具有时滞和反应扩散项的忆阻神经网络（MNN）的全局指数同步问题。首先，利用钉扎控制技术，引入了两种新的控制方法来实现具有时滞和反应扩散项的 MNN 的同步。然后，借助不等式技术、钉扎控制技术、驱动-响应概念和 Lyapunov 函数方法，得到了两个以代数不等式形式表示的充分条件，这些条件可用于确保所提出的具有时滞和反应扩散项的 MNN 的指数同步。此外，基于代数不等式补集得到的结果改进了先前已知的结果。最后，给出了两个实例来说明所得到的理论结果的有效性和正确性。
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