Global asymptotic stability of anti-periodic solution for impulsive Cohen-Grossberg neural networks with multiple delays

Q. Ma, Xinyu Pan, Sitian Qin
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引用次数: 2

Abstract

The global asymptotic stability of anti-periodic solution for Cohen-Grossberg neural networks (CGNNs) is investigated. The CGNNs we consider have impulsive effects and multiple delays. By constructing a suitable Lyapunov function, we prove the existence of the globally asymptotically stable anti-periodic solution for impulsive CGNNs. Several numerical examples are presented to illustrate the validity and improvement of our results.
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多时滞脉冲Cohen-Grossberg神经网络反周期解的全局渐近稳定性
研究了Cohen-Grossberg神经网络反周期解的全局渐近稳定性。我们考虑的cgnn具有脉冲效应和多重延迟。通过构造一个合适的Lyapunov函数,证明了脉冲型cgnn全局渐近稳定反周期解的存在性。最后给出了几个数值算例,说明了所得结果的有效性和改进。
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