Recent Advances on Dynamical Behaviors of Coupled Neural Networks With and Without Reaction-Diffusion Terms
Recent Advances on Dynamical Behaviors of Coupled Neural Networks With and Without Reaction-Diffusion Terms
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DOI：
10.1109/tnnls.2020.2964843
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发表时间：
2020-12-01
影响因子：
10.4
通讯作者：
Huang, Tingwen
中科院分区：
文献类型：
--
作者：
Wang, Jin-Liang;Qiu, Shui-Han;Huang, Tingwen
近年来，由于耦合神经网络在不同领域的成功应用，具有和不具有反应扩散项的耦合神经网络的动力学行为得到了广泛的研究。本文介绍了一些重要的和有趣的结果在这个话题上。首先，同步，无源性和稳定性分析结果的各种CNN与和没有反应扩散项进行了总结，包括脉冲，时变，时不变，不确定，模糊和随机网络模型的结果。此外，一些控制方法，如采样数据控制，钉扎控制，脉冲控制，状态反馈控制，和自适应控制，已被用来实现所需的动力学行为的CNN和没有反应扩散条款。本文对这些方法进行了综述。最后，讨论了一些具有挑战性和有趣的问题，值得进一步研究。
Recently, the dynamical behaviors of coupled neural networks (CNNs) with and without reaction-diffusion terms have been widely researched due to their successful applications in different fields. This article introduces some important and interesting results on this topic. First, synchronization, passivity, and stability analysis results for various CNNs with and without reaction-diffusion terms are summarized, including the results for impulsive, time-varying, time-invariant, uncertain, fuzzy, and stochastic network models. In addition, some control methods, such as sampled-data control, pinning control, impulsive control, state feedback control, and adaptive control, have been used to realize the desired dynamical behaviors in CNNs with and without reaction-diffusion terms. In this article, these methods are summarized. Finally, some challenging and interesting problems deserving of further investigation are discussed.