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Stability and Synchronization for Discrete-Time Complex-Valued Neural Networks with Time-Varying Delays

机译:具有时变时滞的离散复值神经网络的稳定性和同步

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摘要

In this paper, the synchronization problem for a class of discrete-time complex-valued neural networks with time-varying delays is investigated. Compared with the previous work, the time delay and parameters are assumed to be time-varying. By separating the real part and imaginary part, the discrete-time model of complex-valued neural networks is derived. Moreover, by using the complex-valued Lyapunov-Krasovskii functional method and linear matrix inequality as tools, sufficient conditions of the synchronization stability are obtained. In numerical simulation, examples are presented to show the effectiveness of our method.
机译:本文研究了一类具有时变时滞的离散时间复值神经网络的同步问题。与以前的工作相比,假定时延和参数随时间变化。通过分离实部和虚部,导出了复值神经网络的离散时间模型。此外,通过使用复值Lyapunov-Krasovskii泛函方法和线性矩阵不等式作为工具,可以获得足够的同步稳定性条件。在数值模拟中,通过实例说明了该方法的有效性。

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