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Periodic Oscillation and Exponential Stability of a Class of Competitive Neural Networks

机译:一类竞争神经网络的定期振荡和指数稳定性

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In this paper, the periodic oscillation and the global exponential stability of a class of competitive neural networks are analyzed. The competitive neural network considered includes the Hopfield networks, Cohen-Grossberg networks as its special cases. Several sufficient conditions are derived for ascertaining the existence, uniqueness and global exponential stability of the periodic oscillatory state of the competitive neural networks with periodic oscillatory input by using the comparison principle and the theory of mixed monotone operator and mixed monotone flow. As corollary of results on the global exponential stability of periodic oscillation state, we give some results on the global exponential stability of the network modal with constant input, which extend some existing results. In addition, we provide a new and efficacious method for the qualitative analysis of various neural networks.
机译:本文分析了一类竞争神经网络的周期性振荡和全球指数稳定性。竞争神经网络被认为包括Hopfield网络,Cohen-Grossberg网络作为其特殊情况。通过使用比较原理和混合单调算子和混合单调流动的定期振荡输入来确定具有定期振荡输入的定期振荡状态的存在,唯一性和全局指数稳定性。作为结果对周期性振荡状态的全局指数稳定性的导体,我们对具有恒定输入的网络模态的全球指数稳定性产生了一些结果,这延长了一些现有结果。此外,我们为各种神经网络的定性分析提供了一种新的和有效的方法。

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