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首页> 外文会议>2011 30th Chinese Control Conference >Existence and exponential stability of periodic solution of discrete-time Cohen-Grossberg neural network with varying delays and impulses
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Existence and exponential stability of periodic solution of discrete-time Cohen-Grossberg neural network with varying delays and impulses

机译：时滞和脉冲变化的离散时间Cohen-Grossberg神经网络周期解的存在性和指数稳定性

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摘要

A class of the discrete-time Cohen-Grossberg neural network model is studied in this paper. By using the properties of ρ -cone and fixed point theorem, Some sufficient conditions to guarantee the uniqueness and global exponential stability of the periodic solution of such networks are established, and the estimated exponential convergence rate is also obtained. The results of this paper are new and they extend and improve previously known results.
机译：本文研究了一类离散时间的Cohen-Grossberg神经网络模型。利用ρ-锥的性质和不动点定理，建立了保证此类网络周期解的唯一性和全局指数稳定性的充分条件，并获得了估计的指数收敛速度。本文的结果是新的，它们扩展并改进了先前已知的结果。

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