IEEE Trans Neural Netw Learn Syst. 2019 Aug;30(8):2434-2448. doi: 10.1109/TNNLS.2018.2884954. Epub 2018 Dec 25.
This paper presents a complex network model consisting of N uncertain reaction-diffusion neural networks with multiple time delays. We analyze the passivity and synchronization of the proposed network model and derive several passivity and synchronization criteria based on some inequality techniques. In addition, by considering the difficulty in achieving passivity (synchronization) in such a network, an adaptive control scheme is also developed to ensure that the proposed network achieves passivity (synchronization). Finally, we design two numerical examples to verify the effectiveness of the derived passivity and synchronization criteria.
本文提出了一个由 N 个具有多个时滞的不确定反应扩散神经网络组成的复杂网络模型。我们分析了所提出的网络模型的被动性和同步性，并基于一些不等式技术推导出了几个被动性和同步性准则。此外，考虑到在这样的网络中实现被动性（同步）的困难，还开发了一种自适应控制方案，以确保所提出的网络实现被动性（同步）。最后，我们设计了两个数值示例来验证所推导的被动性和同步性准则的有效性。
