一类具有垂直传染的传染病模型的稳定性

基于动力系统的理论,讨论了一类具有垂直传染的传染病模型的稳定性.采用下一代矩阵法获得了基本再生数R₀.当R₀<1时,由Routh-Hurwitz判别法,得到了无病平衡点的局部渐近稳定性.通过构造Lyapunov函数,证明了系统在无病平衡点全局渐近稳定.当R₀> 1时,地方病平衡点存在且唯一,借助Routh判据,得出了系统在地方病平衡点局部渐近稳定的条件,并通过构造Lyapunov函数,证明了系统在地方病平衡点全局渐近稳定.最后,用数值模拟验证了结论的合理性.     

具有毒素和捕获作用的两种群竞争系统的稳定性分析

研究一类两种群无差别捕获的具有毒素作用的竞争系统.首先得到了系统存在唯一正平衡点的充分性条件;其次,通过构造适当的Lyapunov函数得到了保证该系统边界平衡点全局稳定的充分性条件;最后,在前人的基础之上得到了系统正平衡点全局渐近稳定的充分性条件,所得结果补充和完善了T.K.Kar和K.S.Chaudhuri的相应结果.     

食饵具有避难所效应的生态-传染病模型的分析

建立并分析了疾病在食饵中传播、食饵考虑避难所效应的捕食与被捕食模型,捕食者不仅捕食感染食饵而且捕食易感食饵.讨论了系统的有界性和各平衡点的存在性,利用Routh-Hurwitz判据分析各平衡点的局部渐进稳定性,通过构造Lyapunov函数证明了各平衡点的全局渐进稳定性,并进行数值模拟以验证结论的正确性.     

具有混合时滞的脉冲复值神经网络的全局μ-稳定性

研究了具有离散变化时滞和无界分布时滞的脉冲复值神经网络的稳定性,在所研究的神经网络中,活动函数仅仅要求满足Lipschitz条件.运用同胚映射原理,证明了具有混合时滞的脉冲复值神经网络平衡点的存在性和唯一性.通过构造Lyapunov-Krasovskii泛函,使用自由权矩阵方法和不等式技巧,获得了网络平衡点的全局μ-稳定性的充分性判据.数值仿真实例验证了结果的有效性.     

具有扩散影响的Hopfield型神经网络的全局渐近稳定性

对具有扩散影响的Hopfield型神经网络平衡点的存在唯一性和全局渐近稳定性进行了研究．在激活函数单调非减、可微且关联矩阵和Liapunov对角稳定矩阵有关时,利用拓扑度理论得到了系统平衡点存在的充分条件．通过构造适当的平均Liapunov函数,分析了系统平衡点的全局渐近稳定性．所得结论表明系统的平衡点(如果存在)是全局渐近稳定的而且也蕴含着系统的平衡点的唯一性．     

含有双时滞量的细胞神经网络的指数稳定性

讨论了一类含有双时滞量的细胞神经网络模型在平衡点的全局指数稳定性问题.通过构造Lyapunov函数,根据Young不等式和Halanay含时滞的微分不等式,在不需要激励函数满足全局Lipschitz条件的情况下,得到了含有双时滞量的细胞神经网络模型在平衡点是全局指数稳定性的一个充分条件的判据.其所得结果包含并改进了原有的结论,并举例说明了该结果的有效性.     

两种群相互竞争的高维SEIR传染病模型全局渐近稳定性

研究了一类两种群相互竞争的非线性高维SEIR传染病数学模型动力学性质,综合利用Lasalle不变集原理,Lyapunov函数,Routh-Hurwitz判据和Krasnoselskii等多种方法,得到了边界平衡点的全局渐近稳定和正平衡点局部渐近稳定的阈值条件.     

具有反应扩散项的变时滞复数域神经网络的指数稳定性

该文研究了一类具有反应扩散项的变时滞复数域神经网络的指数稳定性.首先在假设复数域激活函数可分解的情况下,将该系统分解为相应的实部系统和虚部系统.利用矢量Lyapunov函数法和M矩阵理论,得到了确保该系统平衡状态指数稳定性的充分条件.该条件不含有任何自由变量,相对现有结论具有较低的保守性.最后通过一个数值仿真算例验证了所得结论的正确性.     

一类具有垂直传染率的SIS模型的稳定性分析

研究了一类具有垂直传染率的SIS模型,首先计算出该模型的基本再生数和平衡点,其次分析了该模型在无病平衡点处的局部渐近稳定性和全局稳定性;然后构造Lyapunov函数证明了地方病平衡点的全局稳定性;最后得到当基本再生数小于1时,传染病会逐渐消失;基本再生数大于1时,传染病将会流行并最终形成一种地方病.     

具有分布时滞的病毒感染模型动力学性质研究

本文研究具有分布时滞的病毒感染模型的动力学性质.构建该模型,基于Lyapunov泛函分析方法,研究该系统平衡点的全局稳定性.分别得到该系统无病平衡点和感染平衡点全局稳定的充分条件.     

Dynamical behaviors of a class of recurrent neural networks with discontinuous neuron activations

This paper investigates the dynamics of a class of recurrent neural networks where the neural activations are modeled by discontinuous functions. Without presuming the boundedness of activation functions, the sufficient conditions to ensure the existence, uniqueness, global exponential stability and global convergence of state equilibrium point and output equilibrium point are derived, respectively. Furthermore, under certain conditions we prove that the system is convergent globally in finite time. The analysis in the paper is based on the properties of M-matrix, Lyapunov-like approach, and the theories of differential equations with discontinuous right-hand side as introduced by Filippov. The obtained results extend previous works on global stability of recurrent neural networks with not only Lipschitz continuous but also discontinuous neural activation functions.     

New optimality conditions for unconstrained vector equilibrium problem in terms of contingent derivatives in Banach spaces

This article presents necessary and sufficient optimality conditions for weakly efficient solution, Henig efficient solution, globally efficient solution and superefficient solution of vector equilibrium problem without constraints in terms of contingent derivatives in Banach spaces with stable functions. Using the steadiness and stability on a neighborhood of optimal point, necessary optimality conditions for efficient solutions are derived. Under suitable assumptions on generalized convexity, sufficient optimality conditions are established. Without assumptions on generalized convexity, a necessary and sufficient optimality condition for efficient solutions of unconstrained vector equilibrium problem is also given. Many examples to illustrate for the obtained results in the paper are derived as well.     

一类变时滞神经网络的全局指数稳定性

本文研究一类变时滞神经网络平衡点的全局指数稳定性.在不要求激活函数全局Lipschitz条件下,利用Lyapunov函数方法,并结合Young不等式和Halanay时滞微分不等式,得到了系统全局指数稳定的充分条件.文末,一个数值例子用以说明本文结果的有效性.     

一类带有一般接触率和常数输入的流行病模型的全局分析

借助极限系统理论和构造适当的Liapunov函数,对带有一般接触率和常数输入的SIR型和SIRS型传染病模型进行讨论．当无染病者输入时,地方病平衡点存在的阈值被找到A·D2对相应的SIR模型,关于无病平衡点和地方病平衡点的全局渐近稳定性均得到充要条件;对相应的SIRS模型,得到无病平衡点和地方病平衡点全局渐近稳定的充分条件．当有染病者输入时,模型不存在无病平衡点．对相应的SIR模型,地方病平衡点是全局渐近稳定的;对相应的SIRS模型,得到地方病平衡点全局渐近稳定的充分条件．     

New results of global robust exponential stability of neural networks with delays

In this paper, the global robust exponential stability of interval neural networks with delays is investigated. Employing homeomorphism techniques and Lyapunov functions, we establish some sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point for delayed neural networks. It is shown that the obtained results improve and generalize the previously published results.     

Probabilistic stability analysis of social obesity epidemic by a delayed stochastic model

Sufficient conditions for stability in probability of the equilibrium point of a social obesity epidemic model with distributed delay and stochastic perturbations are obtained. The obesity epidemic model is demonstrated on the example of the Region of Valencia, Spain. The considered nonlinear system is linearized in the neighborhood of the positive point of equilibrium and a sufficient condition for asymptotic mean square stability of the zero solution of the constructed linear system is obtained.     

Global dynamics of a modified Leslie-Gower predator-prey model with Crowley-Martin functional responses

In this paper, we study a modified Leslie-Gower predator-prey model with Crowley-Martin functional responses. We show the existence of a bounded positive invariant and attracting set. The possibility of existence and uniqueness of positive equilibrium are considered. The asymptotic behavior of the positive equilibrium and the existence of Hopf-bifurcation of nonconstant periodic solutions surrounding the interior equilibrium are considered. The existence and non-existence of periodic solutions are established under suitable conditions. The permanence conditions are also established. We obtained sufficient conditions to ensure the global stability of the unique positive equilibrium, by using suitable Lyapunov functions, LaSalle invariance principle and Dulac’s criterion. We obtained also sufficient conditions for the global stability of the prey-extinction equilibrium when the unique positive equilibrium is not feasible. Finally, numerical simulations are presented to illustrate the analytical results.     

Global exponential stability of reaction-diffusion cellular neural networks with S-type distributed time delays

The authors discuss the existence of the equilibrium point and its global exponential stability of reaction-diffusion cellular neural networks (RDCNNs) with S-type distributed signal transmission delays along the axon of a neuron by means of the topological degree theory and differential inequality technique. A theorem and two corollaries were obtained in which the boundedness, monotonicity and differentiability conditions on the activation functions are not required. The sufficient conditions on global exponential stability established in this paper, which are easily verifiable, have a wider adaptive range.