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Pseudo almost periodic solutions for neutral type high-order Hopfield neural networks with mixed time-varying delays and leakage delays on time scales

机译:时标混合时变时滞和泄漏时滞的中立型高阶Hopfield神经网络的伪几乎周期解

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摘要

We propose a class of neutral type high-order Hopfield neural networks with mixed time-varying delays and leakage delays on time scales. Applying the exponential dichotomy of linear dynamic equations on time scales, Banach's fixed point theorem and theory of calculus on time scales, we obtain several sufficient conditions to ensure the existence and global exponential stability of pseudo almost periodic solutions of the proposed neural networks. Finally, we illustrate the effectiveness of the obtained results with an example. The example also shows that the continuous-time neural network and its discrete-time analogue have the same dynamical behaviors when considering the pseudo almost periodicity.
机译:我们提出一类在时标上具有混合时变时滞和泄漏时滞的中立型高阶Hopfield神经网络。应用时标上的线性动力学方程的指数二分法,时标上的Banach不动点定理和演算理论,我们获得了几个充分的条件,以确保拟议神经网络的伪几乎周期解的存在性和全局指数稳定性。最后,我们通过一个例子来说明所获得结果的有效性。该示例还表明,当考虑伪几乎周期性时,连续时间神经网络及其离散时间模拟具有相同的动力学行为。

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