时变时滞随机反应-扩散神经网络的稳定性和p- laplace

IF 1.2 Q2 MATHEMATICS, APPLIED

Journal of Applied Mathematics Pub Date : 2012-12-03 DOI:10.1155/2012/405939

Pan Qingfei, Zhang Zi-fang, Huang Jingchang

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引用次数: 8

摘要

本文的主要目的是讨论具有时变时滞和p-拉普拉斯算子的随机反应-扩散神经网络的矩指数稳定性。利用伊藤公式、一个时滞微分不等式和神经网络的特性，导出了非常平衡解矩指数稳定的代数条件。还给出了一个例子来说明。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Stability of the Stochastic Reaction-Diffusion Neural Network with Time-Varying Delays and p-Laplacian

The main aim of this paper is to discuss moment exponential stability for a stochastic reaction-diffusion neural network with time-varying delays and p-Laplacian. Using the Ito formula, a delay differential inequality and the characteristics of the neural network, the algebraic conditions for the moment exponential stability of the nonconstant equilibrium solution are derived. An example is also given for illustration.

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来源期刊

Journal of Applied Mathematics MATHEMATICS, APPLIED-

CiteScore

2.70

自引率

0.00%

发文量

审稿时长

3.2 months

期刊介绍： Journal of Applied Mathematics is a refereed journal devoted to the publication of original research papers and review articles in all areas of applied, computational, and industrial mathematics.