带有分段常数变量的Lorenz系统的稳定性和分支

本文研究一类带有分段常数变量的Lorenz系统的稳定性和分支行为.首先通过计算转化得到Lorenz系统对应的差分系统,利用线性稳定性理论讨论平衡点局部渐近稳定的充要条件.其次选择差分系统三个参数的一个参数为分支参数,利用分支理论研究平衡点处产生Neimark-Sacker分支不变闭曲线的充要条件,并使用分支理论给出判断分支不变闭曲线的稳定性的阈值.最后数值模拟验证了理论分析的正确性.     

二维不可压缩Navier-Stokes方程的七模类Lorenz方程组的动力学行为及其数值模拟

本文研究了平面不可压缩的Navier-Stokes方程一个七模类Lorenz方程组的混沌行为问题.利用模式截断的方法,获得了一个七模类Lorenz方程组,证明了该方程组吸引子的存在性,并对其全局稳定性进行了分析和讨论.基于分岔图、最大李雅普诺夫指数、庞加莱截面、功率谱揭示了系统混沌行为的普适特征,仿真分析了系统动力学行为的演化过程.     

单时滞类Lorenz系统的Hopf分岔分析

本文研究单时滞类Lorenz系统的稳定性问题.利用规范型理论,分析该系统在其零平衡点处的稳定性和发生Hopf分岔的条件,并通过数值仿真验证所得结论的正确性.本文的结论可以看做是对文献[5]研究成果的推广.     

同心球间流动三模类Lorenz系统的动力学行为及数值仿真

讨论了同心球间旋转流动的类Lorenz型方程组的动力学行为及其数值模拟问题,求出了该方程组平衡点,并对其稳定性进行了分析,证明了该方程组吸引子的存在性,对类Lorenz方程组的动力学行为进行了数值模拟,数值试验表明此类Lorenz型方程组存在极限环和奇怪吸引子.     

Couette-Taylor流三模系统的混沌行为及其仿真

研究了旋流式Couette-Taylor流三模态类Lorenz系统的动力学行为及其数值仿真问题.给出了此系统平衡点存在的条件,证明了其吸引子的存在性,给出了吸引子的Hausdorff维数上界的估计,数值模拟了系统分歧和混沌等的动力学行为发生的全过程,基于分岔图与最大Lyapunov指数谱和庞加莱截面以及功率谱和返回映射等仿真结果揭示了此系统混沌行为的普适特征.     

时滞扰动类Lorenz系统的Hopf分岔

通过非线性动力学理论,对时滞类Lorenz系统在平衡点的稳定性问题和发生Hopf分岔的条件进行了研究.首先计算得到系统的平衡点,然后通过分析系统在平衡点处的相应特征方程根的分布,得到系统在平衡点局部渐近稳定和产生Hopf分岔的时滞临界点.以时滞为分叉参数,研究了时滞系统存在Hopf分岔的条件.最后,利用Matlab程序进行仿真验证所得结论与理论分析一致.本文的结论是对一些已有文献研究成果的推广.     

磁流体动力学截断方程组的动力学行为研究

本文研究了平面正方形区域上不可压缩的磁流体动力学方程组的动力学行为问题.利用模式截断的方法,获得了一个全新的十模类Lorenz方程组,求得了此方程组的平衡点,分析了其稳定性等动力学行为,证明了该类Lorenz方程组混沌吸引子的存在性,并对其动力学行为进行了数值模拟.     

N个异结构混沌系统的环链耦合同步

提出了一种通过环链耦合实现N个异结构混沌系统同步的方法.以New系统、Chen系统、Lü系统、Lorenz系统和Rssler系统作为典型的例子,验证了这种同步控制方法的有效性.利用Liapunov稳定性定理,构造控制器的具体形式,并确定了耦合系数的取值范围.仿真模拟结果表明,在控制器的作用下,选择适当的耦合系数值,可以同时使N个异结构混沌系统达到完全同步.     

旋转流动的低模分析及仿真研究

为了探讨Couette-Taylor流从层流到湍流过渡的方式以及流动发展到湍流之后混沌吸引子的某些特征等问题,采用低模分析方法研究了Couette-Taylor流的部分动力学行为及仿真问题,讨论了Couette-Taylor流三模态类Lorenz型方程组的动力学行为,包括定态的失稳、极限环的出现、分岔与混沌的演变和全局稳定性分析等。通过线性稳定性分析和数值模拟等方法给出了此三维模型分岔与混沌等动力学行为及其演化历程,并借此解释了Couette-Taylor流试验中观察到的部分涡流的演化过程.基于系统的分岔图、Lyapunov指数谱、功率谱、Poincaré(庞加莱)截面和返回映射等揭示了系统混沌行为的普适特征.     

一类具有阶段结构的食物链系统

研究了一类具有阶段结构的食物链模型,分析了系统平衡点的稳定性,运用数值模拟展示了系统周期性振动,混沌等复杂的动力学行为,并分析了阶段结构对系统复杂行为的影响.     

Meritocratic and monopoly inequality: A computer simulation of income distribution

This paper explores the properties of a model of the distribution of income in which individual income is proportional to a multiplicative function of previous income, ability, chance, a ceiling factor determined by competition among members of an income class for resources held by members of other classes, and an additive factor summarizing effects of altruism and minimal subsistence. The behavior of the model is investigated by computer simulation for combinations of values of three model parameters representing the tendency of income to grow exponentially (the Monopoly effect), the weight of the ability factor (the meritocracy effect), and the weight of the ceiling factor resulting from competitive interactions. Steady state income distributions generated by the model are characterized by measures of income inequality, exchange mobility, elite stability, and meritocracy. Results suggest that for constant Monopoly effect, the effect of the meritocracy parameter on various aggregate outcomes is nonlinear, with a range over which greater returns to ability produce lower inequality, lower exchange mobility, greater elite stability and meritocracy, for constant returns to ability, a greater Monopoly effect generally produces greater inequality, more exchange mobility, less stability of the elite, and lower meritocracy. Results also reveal a nonlinear relationship between exchange mobility and inequality, with mobility decreasing to a minimum and then increasing again as inequality increases; a nonlinear but monotonic negative relationship between elite stability and inequality, with greater inequality, associated with less stability, and a nonlinear relationship between meritocracy and inequality, with meritocracy increasing at first with inequality at low inequality levels, reaching a maximum and then decreasing as inequality increases further. These findings are interpreted in relation to major stratification trends in the course of sociocultural evolution.     

Stability analysis for variational inequality in reflexive Banach spaces

This paper is devoted to the stability analysis in variational inequality. We obtain some stability results for variational inequality with both the mapping and the set that are perturbed in reflexive Banach spaces, provided that the mappings are pseudomonotone in the sense of Karamardian. The stability is also discussed for the Minty variational inequality as the mappings are properly quasimonotone. The results in this paper generalized some known results in this area.     

Stability of some versions of the Prékopa–Leindler inequality

Two consequences of the stability version of the one dimensional Prékopa–Leindler inequality are presented. One is the stability version of the Blaschke–Santaló inequality, and the other is a stability version of the Prékopa– Leindler inequality for even functions in higher dimensions, where a recent stability version of the Brunn–Minkowski inequality is also used in an essential way.     

Functional inequalities in non-Archimedean normed spaces

In this paper, we introduce an additive functional inequality and a quadratic functional inequality in normed spaces, and prove the Hyers–Ulam stability of the functional inequalities in Banach spaces. Furthermore, we introduce an additive functional inequality and a quadratic functional inequality in non-Archimedean normed spaces, and prove the Hyers–Ulam stability of the functional inequalities in non-Archimedean Banach spaces.     

基于一类积分不等式上的中立型时滞微分方程的稳定性

利用一类积分不等式以及参数变易法,Jensen不等式,给出了更为一般的中立型时滞微分系统的Lyapunov稳定性的判别准则,推广和改进了一些文献中有关中立型微分方程的Lyapunov稳定性的结论.     

Exponential stability for nonautonomous neural networks with variable delays

In this paper, by utilizing a delay differential inequality and combining with inequality analysis technique, we investigate global exponential stability for nonautonomous neural networks with variable delays. Some new sufficient conditions ensuring global exponential stability are obtained. An example is also given to demonstrate the effectiveness of the obtained results.     

广义Ky Fan点的通有稳定性

得到一个广义的Ky Fan不等式,它以通常的Ky Fan不等式为特例.我们讨论了在一致度量诱导的拓扑结构和二元泛函上方图形的拓扑结构下广义Ky Fan不等式问题构成的空间M中,大多数(在Baire分类意义下)广义Ky Fan不等式问题的所有广义Ky Fan点都是稳定的.     

Veljan-Korchmaros不等式的稳定性

关于Euclidean空间E~n(n■2)中单形的几何不等式,由于支撑函数或径向函数的表达式很难找到,因此一般很难用Hausdorff度量或径向度量来度量两个单形的"偏差",使得涉及单形的几何不等式的稳定性的研究一直为空白.本文利用单形棱长在确定单形时起决定性作用这一事实,引进了两个单形"偏正"度量的概念,从而较好地解决了单形偏正度量的问题,由此建立了著名的Veljan-Korchmaros不等式的稳定性版本,作为推论,导出了单形中著名的Weitzenb■ck不等式和Euler不等式的稳定性版本,最后提出了几个有待解决的问题.     

Global exponential stability of impulsive discrete-time neural networks with time-varying delays

This paper studies the problem of global exponential stability and exponential convergence rate for a class of impulsive discrete-time neural networks with time-varying delays. Firstly, by means of the Lyapunov stability theory, some inequality analysis techniques and a discrete-time Halanay-type inequality technique, sufficient conditions for ensuring global exponential stability of discrete-time neural networks are derived, and the estimated exponential convergence rate is provided as well. The obtained results are then applied to derive global exponential stability criteria and exponential convergence rate of impulsive discrete-time neural networks with time-varying delays. Finally, numerical examples are provided to illustrate the effectiveness and usefulness of the obtained criteria.     

Dynamics of a hysteretic neuron model

A mathematical model of a single isolated artificial neuron with hysterisis is formulated by means of a neutral delay differential equation. The asymptotic and exponential stability of such a model are investigated. Sufficient conditions for the exponential stability of a linear integral difference inequality are obtained. In the absence of hysterisis effect, our model reduces to a known model of a single neuron. Usually asymptotic stability of neutral delay differential equations is studied by means of degenerate Lyapunov–Kravsovskii functionals. In this article, perhaps for the first time exponential stability of a class of neutral differential equations are studied by means of the exponential stability of an affiliated difference inequality. While generalization to Hopfield type hysteretic neural networks is possible, such a generalization is not considered in this article.