变时滞Hopfield神经网络的全局吸引性和全局指数稳定性

对一类具时滞的Hopfeild型神经网络模型,在非线性神经元激励函数只要求满足Lipschitz连续的条件下,利用推广的Halanay时延微分析不等式、Dini导数以及泛函微分析技术,给出了这类模型的平衡点全局指数稳定性和全局吸引性的充分条件,这些条件易于检验,且改进和推广了前人的结论.此外,此文给出了研究神经网络模型的全局吸引性的微分不等式比较方法.     

一类SIQA模型解的全局稳定性

讨论用脉冲隔离的方案控制HIV的传播.假定艾滋病感染者发展成艾滋病人和感染年龄有关,我们建立了带脉冲隔离类和感染年龄的HIV模型.在一定条件下证明该模型的无病平衡态是全局稳定的.     

多因素指派模型全局优化问题研究

基于多因素资源优化分配问题的不确定性,建立基于区间数型下的不确定多因素指派模型,给出模型建立的理论依据与全局优化算法,拓展区间数型多因素指派模型,解决了不确定条件下多因素资源优化分配问题.考虑多因素影响,基于任务完成效率,以5类任务多因素分配问题为例,获得了指派模型全局优化的解.为不确定条件下资源优化分配问题的研究拓宽了决策途径.     

一类微分方程零解全局弱吸引和全局吸引到充要条件

考虑二阶微分方程 x =φ(y)-F(x),y=- g(x)q(y) 零解的全局弱吸引和全局吸引性, 说明了Filippov条件(A₂) 不能排除最大椭圆扇形S^* 的存在性, 也不能排除∂S^* 作为其外侧邻域轨线正向极限集的可能. 全面回答了文献[8]末提出的问题;得到了方程(E)满足或不满足Filippov 条件时零解全局弱吸引和全局吸引的一系列充分必要条件, 同时也得到了零解全局渐近稳定的一些新条件.     

记忆型梁方程强解的全局吸引子

记忆型梁方程出现于—般的Kirchhoff粘弹性梁模型中．本文在记忆核满足指数衰退的条件下证明了系统的能量也是指数衰退的．进一步,通过对条件(C)的验证获得了系统强解的全局吸引子．     

具有年龄结构的离散HIV/AIDS模型的全局分析

本文根据艾滋病传播的特点建立了有年龄结构的高维离散SIA模型,和有干预的具有年龄结构的离散HIV模型.对每种模型,我们首先给出了建模思想,用差分方程建立了数学模型,然后对模型平衡点的稳定性进行了理论分析,得出一定条件下模型无病平衡点和地方病平衡点的稳定性.另外,本文还给出了模型的基本再生数,其意义为一个病人在染病期内平均感染的人数,基本再生数决定了模型无病平衡点和地方病平衡点的存在性和稳定性.     

变时滞BAM神经网络的全局指数稳定性

研究一类变时滞BAM神经网络平衡点的全局指数稳定性问题.在不要求激励函数全局Lipschitz条件下,通过构造合适的Lyapunov泛函,并结合Young不等式,得到了BAM神经网络模型在一定条件下全局指数稳定的一些充分条件,推广和改进了前人的相关结论,为综合设计指数稳定的时滞BAM神经网络提供了依据.     

具有时滞的单种群扩散模型的全局稳定性

该文研究了一类具有时滞的单种群扩散模型, 利用同伦技术得到了模型存在正平衡点. 在适当的条件下证明了系统是一致持续的, 获得了系统的正平衡点的局部和全局稳定性的充分条件.     

海洛因传染病模型的确定性与随机性的全局分析

建立海洛因传染病模型.证明无毒平衡点在一定条件下是全局稳定的.对随机模型,证明解的全局存在和正性,证明在强烈的白噪声扰动下,无毒平衡点以概率和p阶矩全局稳定.     

三种群Lotka-Volterra周期系数混合模型的全局渐近稳定性

本文考虑周期系数的三种群 Lokta-Volterra模型 ,种群间既有捕食关系又有竞争关系 ,得到其正周期解的存在性及其全局渐近稳定性的条件 ,且举例说明条件的可行性     

Global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays

In this paper, by means of constructing the extended impulsive delayed Halanay inequality and by Lyapunov functional methods, we analyze the global exponential stability and global attractivity of impulsive Hopfield neural networks with time delays. Some new sufficient conditions ensuring exponential stability of the unique equilibrium point of impulsive Hopfield neural networks with time delays are obtained. Those conditions are more feasible than that given in the earlier references to some extent. Some numerical examples are also discussed in this work to illustrate the advantage of the results we obtained.     

含脉冲的Hopfield神经网络的全局指数稳定性

研究了一类含脉冲的Hopfield神经网络的全局指数稳定性.利用同胚映射理论、Lyapunov函数思想和不等式技巧,给出了平衡点的存在唯一性和全局指数稳定性的新的判别准则.     

GLOBAL ATTRACTIVITY OF THE HOPFIELD NEURAL NETWORKS

1 IntroductionHopfield neural networks is an associative memory model, it is also a neuraloptimization networks. This model has been studied extensively (see [1--12]).But in most of the literature, the signal function gi(x) is differentiable and isa sigmoid curve, and the sufficient conditions about the global attractivity ofthe Hopfield neural networks have no relevance to the delay. The aim of thispaper is to give a delayed sufficient condition of the global attractivity of theHopfield neur…     

STABILITY ANALYSIS OF HOPFIELD NEURAL NETWORKS WITH DELAYS

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Hopfield神经网络的周期解存在性及其全局吸引性

利用重合度理论和微分不等式分析等技巧，给出了Hopfield神经网络周期解存在性及其全局吸引性的判别准则。     

Global exponential stability in Lagrange sense for recurrent neural networks with time delays

In this paper, we study the global exponential stability in Lagrange sense for continuous recurrent neural networks (RNNs) with multiple time delays. Three different types of activation functions are considered, which include both bounded and unbounded activation functions. By constructing appropriate Lyapunov-like functions, we provide easily verifiable criteria for the boundedness and global exponential attractivity of RNNs. These results can be applied to analyze monostable as well as multistable neural networks.     

Existence and global exponential stability of almost periodic solution for quaternion-valued high-order Hopfield neural networks with delays via a direct method

This paper deals with the existence and global exponential stability of almost periodic solutions for quaternion-valued high-order Hopfield neural networks with delays by a direct approach. Based on the contraction mapping principle, sufficient conditions are derived to ensure the existence and uniqueness of almost periodic solutions for the networks under consideration. By constructing a suitable Lyapunov function, the global exponential stability criterion of the almost periodic solution are derived. Finally, two numerical examples are given to illustrate the main results of this paper.     

时滞Hopfield神经网络的全局指数稳定性

讨论带有可变时滞的Hopfield神经网络的全局指数稳定性.在非线性激励函数满足Lipschitz条件的假设下,利用推广的Halanay不等式,Dini导数和分析技巧,建立了这类神经网络系统全局指数稳定的几个判别准则.这些判别准则仅仅依赖于系统的参数.     

Global stability analysis in hopfield neural networks

In this paper, one approach is employed to investigate the existence and uniqueness of the equilibrium and the global attractivity of Hopfield neural network models. Without assuming the boundedness, monotonicity, and differentiability of the activation functions, by using M-matrix theory, Liapunov functions are constructed and employed to establish sufficient conditions for global asymptotic stability.