具有泄漏、混合时间延迟和 α 逆霍尔德激活函数的马尔可夫跳跃随机脉冲不确定 BAM 神经网络的全局指数稳定性。

IF 4.1 3区 数学 Q1 Mathematics
Advances in Difference Equations Pub Date : 2018-01-01 Epub Date: 2018-03-27 DOI:10.1186/s13662-018-1553-7
C Maharajan, R Raja, Jinde Cao, G Ravi, G Rajchakit
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引用次数: 0

摘要

本文涉及具有泄漏延迟的不确定离散时间马尔可夫跃迁 BAM 延迟神经网络的鲁棒有限时间通过性的增强结果问题。通过采用适当的 Lyapunov-Krasovskii 候选函数、互凸组合方法和线性矩阵不等式技术,我们推导出了改变离散时间 BAM 神经网络被动性的几个充分条件。此外,通过使用零不等式,我们还提出了一些有限时间有界性和不确定性被动性的充分条件。最后,我们通过数值示例和仿真演示了所提标准可行区域的增强,以说明所提方法的适用性和实用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and <i>α</i>-inverse Hölder activation functions.

Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and <i>α</i>-inverse Hölder activation functions.

Global exponential stability of Markovian jumping stochastic impulsive uncertain BAM neural networks with leakage, mixed time delays, and α-inverse Hölder activation functions.

This paper concerns the problem of enhanced results on robust finite time passivity for uncertain discrete time Markovian jumping BAM delayed neural networks with leakage delay. By implementing a proper Lyapunov-Krasovskii functional candidate, reciprocally convex combination method, and linear matrix inequality technique, we derive several sufficient conditions for varying the passivity of discrete time BAM neural networks. Further, some sufficient conditions for finite time boundedness and passivity for uncertainties are proposed by employing zero inequalities. Finally, the enhancement of the feasible region of the proposed criteria is shown via numerical examples with simulation to illustrate the applicability and usefulness of the proposed method.

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来源期刊
自引率
0.00%
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0
审稿时长
4-8 weeks
期刊介绍: The theory of difference equations, the methods used, and their wide applications have advanced beyond their adolescent stage to occupy a central position in applicable analysis. In fact, in the last 15 years, the proliferation of the subject has been witnessed by hundreds of research articles, several monographs, many international conferences, and numerous special sessions. The theory of differential and difference equations forms two extreme representations of real world problems. For example, a simple population model when represented as a differential equation shows the good behavior of solutions whereas the corresponding discrete analogue shows the chaotic behavior. The actual behavior of the population is somewhere in between. The aim of Advances in Difference Equations is to report mainly the new developments in the field of difference equations, and their applications in all fields. We will also consider research articles emphasizing the qualitative behavior of solutions of ordinary, partial, delay, fractional, abstract, stochastic, fuzzy, and set-valued differential equations. Advances in Difference Equations will accept high-quality articles containing original research results and survey articles of exceptional merit.
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