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Delay-independent exponential stability of stochastic Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms

机译:时变时滞和反应扩散项的随机Cohen-Grossberg神经网络的时滞无关指数稳定性

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摘要

Different from the approaches used in the earlier papers, in this paper, the Halanay inequality technique, in combination with the Lyapunov method, is exploited to establish a delay-independent sufficient condition for the exponential stability of stochastic Cohen-Grossberg neural networks with time-varying delays and reaction-diffusion terms. Moreover, for the deterministic delayed Cohen-Grossberg neural networks, with or without reaction-diffusion terms, sufficient criteria for their global exponential stability are also obtained. The proposed results improve and extend those in the earlier literature and are easier to verify. An example is also given to illustrate the correctness of our results.
机译:与先前论文中使用的方法不同,本文采用Halanay不等式技术与Lyapunov方法相结合,为时滞随机Cohen-Grossberg神经网络的指数稳定性建立了与时延无关的充分条件。变化的延迟和反应扩散项。此外,对于具有或不具有反应扩散项的确定性延迟Cohen-Grossberg神经网络,也可以获得其全局指数稳定性的充分标准。拟议的结果改进和扩展了早期文献中的结果,并且更易于验证。还给出了一个例子来说明我们的结果的正确性。

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