Stability and convergence analysis for a class of neural networks.

IEEE transactions on neural networks Pub Date : 2011-11-01 Epub Date: 2011-09-29 DOI:10.1109/TNN.2011.2167760
Xingbao Gao, Li-Zhi Liao
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引用次数: 2

Abstract

In this paper, we analyze and establish the stability and convergence of the dynamical system proposed by Xia and Feng, whose equilibria solve variational inequality and related problems. Under the pseudo-monotonicity and other conditions, this system is proved to be stable in the sense of Lyapunov and converges to one of its equilibrium points for any starting point. Meanwhile, the global exponential stability of this system is also shown under some mild conditions without the strong monotonicity of the mapping. The obtained results improve and correct some existing ones. The validity and performance of this system are demonstrated by some numerical examples.

一类神经网络的稳定性与收敛性分析。
本文分析并建立了Xia和Feng提出的求解变分不等式及相关问题的动力系统的稳定性和收敛性。在伪单调性等条件下,证明了该系统在Lyapunov意义上是稳定的,并对任意起始点收敛于其平衡点之一。同时,在不存在强单调性的条件下,也证明了该系统的全局指数稳定性。所得结果是对已有结果的改进和修正。通过数值算例验证了该系统的有效性和性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE transactions on neural networks
IEEE transactions on neural networks 工程技术-工程:电子与电气
自引率
0.00%
发文量
2
审稿时长
8.7 months
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