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Global Exponential Synchronization of Complex-Valued Neural Networks with Time Delays via Matrix Measure Method

机译:时滞复值神经网络的全局指数同步的矩阵测度

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摘要

In this paper, global exponential synchronization of a class of complex-valued neural networks with time delays is investigated. Based on Halanay inequality theory, Lyapunov theory and matrix measure method, by separating complex-valued neural networks to the real part and imaginary part, several criteria for the global exponentially synchronization of complex-valued neural networks are presented. Finally, one numerical simulation is given to show the effectiveness of our theoretical results.
机译:本文研究了一类具有时滞的复值神经网络的全局指数同步。基于Halanay不等式理论,Lyapunov理论和矩阵度量方法,通过将复值神经网络分为实部和虚部,提出了复值神经网络的全局指数同步的几个准则。最后,给出了一个数值模拟来证明我们理论结果的有效性。

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