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Exponential and fixed-time synchronization of Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms

机译:Cohen-Grossberg神经网络具有时变延迟和反应扩散条款的指数和定时同步

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This paper is devoted to the global exponential and fixed-time synchronization of delayed reaction-diffusion Cohen-Grossberg neural networks. Adaptive controllers are designed such that the addressed system can realize global exponential synchronization goal under the framework of inequality techniques, Lyapunov method as well as some suitable assumptions. Furthermore, as corollaries, the corresponding conclusion is provided to ensure the delayed Cohen-Grossberg neural networks without reaction-diffusion term can reach fixed-time synchronization goal. In addition, the settling time of fixed-time synchronization can be adjusted to desired values regardless of initial conditions, which is more reasonable. Finally, two numerical examples and its simulations are given to show the effectiveness of the obtained results. (C) 2017 Elsevier Inc. All rights reserved.
机译:本文致力于延迟反应扩散COHEN-GROSSBERG神经网络的全球指数和定期同步。 自适应控制器被设计成使得寻址系统可以根据不等式技术框架实现全球指数同步目标,Lyapunov方法以及一些合适的假设。 此外,作为冠状石,提供了相应的结论,以确保没有反应扩散术语的延迟的Cohen-Grossberg神经网络可以达到定时同步目标。 另外,无论初始条件如何,都可以调整固定时间同步的稳定时间,这是更合理的。 最后,给出了两个数值例子及其模拟以显示所获得的结果的有效性。 (c)2017年Elsevier Inc.保留所有权利。

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