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Finite-time synchronization of memristor-based Cohen-Grossberg neural networks with time-varying delays

机译:具有时变时滞的基于忆阻器的Cohen-Grossberg神经网络的有限时间同步

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摘要

This paper concerns the problem of global and local finite-time synchronization for a class of memristor-based Cohen-Grossberg neural networks with time-varying delays by designing an appropriate feedback controller. Through a nonlinear transformation, we derive an alternative system from the considered memristor-based Cohen-Grossberg neural networks. Then, by considering the finite-time synchronization of the alternative system, we obtain some novel and effective finite-time synchronization criteria for the considered memristor-based Cohen-Grossberg neural networks. These results generalize and extend some previous known works on conventional Cohen-Grossberg neural networks. Finally, numerical simulations are given to present the effectiveness of the theoretical results. (C) 2016 Elsevier B.V. All rights reserved.
机译:本文通过设计适当的反馈控制器,针对一类具有时变时滞的基于忆阻器的Cohen-Grossberg神经网络,研究了全局和局部有限时间同步的问题。通过非线性变换,我们从考虑的基于忆阻器的Cohen-Grossberg神经网络中得出了一个替代系统。然后,通过考虑替代系统的有限时间同步,我们为考虑的基于忆阻器的Cohen-Grossberg神经网络获得了一些新颖有效的有限时间同步准则。这些结果概括并扩展了传统Cohen-Grossberg神经网络上的一些先前已知的工作。最后,数值模拟给出了理论结果的有效性。 (C)2016 Elsevier B.V.保留所有权利。

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