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Global exponential stability of periodic solutions for impulsive Cohen-Grossberg neural networks with delays

机译:时滞脉冲Cohen-Grossberg神经网络周期解的全局指数稳定性

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摘要

By constructing appropriate Lyapunov functions and using some inequality techniques and a fixed point theorem, some sufficient conditions are obtained to ensure the existence and global exponential stability of periodic solutions for impulsive Cohen-Grossberg neural networks with delays. The boundedness of the activation functions is not assumed. The criteria given can be easily verified and possess many adjustable parameters, which provide flexibility for the design and analysis of the system. Several previous results are improved and two examples are given to demonstrate the effectiveness of the theoretical results.
机译:通过构造适当的Lyapunov函数并使用一些不等式技术和不动点定理,可以获得一些充分的条件,以确保带时滞的脉冲Cohen-Grossberg神经网络周期解的存在性和全局指数稳定性。不假定激活函数的有界性。给出的标准很容易验证,并具有许多可调整的参数,这为系统的设计和分析提供了灵活性。改进了先前的几个结果,并给出了两个例子来证明理论结果的有效性。

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