随机环境中马氏链的常返性和瞬时性

讨论了随机环境马氏链中具有强π不可约性链的常返性的判定,从而得到了强π不可约链常返性判定的充分必要条件,同时给出了在一定条件下随机环境中的马氏链的瞬时性判定的几个充分条件.     

1961～2005年漠河年均温和年均高低温的变化分析

对近四十五年来中国漠河的气温变化作了一个初步分析.根据中国漠河1961～2005年逐日平均、最高、最低气温资料,求得了相应的年均温、年均高温和年均低温,分别对它们进行了线性拟合,结果表明它们在这45年都有所升高,并且由t检验得出线性趋势都是显著的.之后用线性回归模型拟合了年均温与年均高温和年均低温的关系,得出了拟合方程,并由F检验说明了线性回归关系的显著性.最后又采用变系数回归模型的局部线性拟合方法拟合了年均温与年均高温和年均低温的变化关系,从而揭示了年均高温和年均低温对年均温的影响随时间变化的规律,对研究年均温升高的原因具有一定的参考意义.     

Spreading and generalized propagating speeds of discrete KPP models in time varying environments

The current paper deals with spatial spreading and front propagating dynamics for spatially discrete KPP (Kolmogorov, Petrovsky and Paskunov) models in time recurrent environments, which include time periodic and almost periodic environments as special cases. The notions of spreading speed interval, generalized propagating speed interval, and traveling wave solutions are first introduced, which are proper modifications of those introduced for spatially continuous KPP models in time almost periodic environments. Among others, it is then shown that the spreading speed interval in a given direction is the minimal generalized propagating speed interval in that direction. Some important upper and lower bounds for the spreading and generalized propagating speed intervals are provided. When the environment is unique ergodic and the so called linear determinacy condition is satisfied, it is shown that the spreading speed interval in any direction is a singleton (called the spreading speed), which equals the classical spreading speed if the environment is actually periodic. Moreover, in such a case, a variational principle for the spreading speed is established and it is shown that there is a front of speed c in a given direction if and only if c is greater than or equal to the spreading speed in that direction.      

随机环境中两性分枝过程的马氏性和对偶性

证明了独立同分布环境中的两性分枝过程是时奇的马氏链,给出了过程灭绝一爆炸这一对偶性的一个新的证明。在随机环境情形下,证明了一类单调函数的存在性。     

Robust stability analysis of stochastic neural networks with Markovian jumping parameters and probabilistic time‐varying delays

This article discusses the issue of robust stability analysis for a class of Markovian jumping stochastic neural networks (NNs) with probabilistic time‐varying delays. The jumping parameters are represented as a continuous‐time discrete‐state Markov chain. Using the stochastic stability theory, properties of Brownian motion, the information of probabilistic time‐varying delay, the generalized Ito's formula, and linear matrix inequality (LMI) technique, some novel sufficient conditions are obtained to guarantee the stochastical stability of the given NNs. In particular, the activation functions considered in this article are reasonably general in view of the fact that they may depend on Markovian jump parameters and they are more general than those usual Lipschitz conditions. The main features of this article are described in the following: first one is that, based on generalized Finsler lemma, some improved delay‐dependent stability criteria are established and the second one is that the nonlinear stochastic perturbation acting on the system satisfies a class of Lipschitz linear growth conditions. By resorting to the Lyapunov–Krasovskii stability theory and the stochastic analysis tools, sufficient stability conditions are established using an efficient LMI approach. Finally, two numerical examples and its simulations are given to demonstrate the usefulness and effectiveness of the proposed results. © 2014 Wiley Periodicals, Inc. Complexity 21: 59–72, 2016     

LMI‐based criterion for the robust guaranteed cost control of uncertain switched neutral systems with time‐varying mixed delays and nonlinear perturbations by dynamic output feedback

This article reports on an investigation into robust guaranteed cost control (GCC) for uncertain switched neutral systems (USNSs) with interval time‐varying mixed delays and nonlinear perturbations via dynamic output feedback. Delay‐dependent sufficient conditions are suggested to guarantee the robust exponential stability and to obtain robust GCC for USNSs using the average dwell time approach and the piecewise Lyapunov function technique in terms of a set of linear matrix inequalities. The problem of uncertainty in the system model is solved by deploying the Yakubovich lemma. Lastly, two examples (i.e., a numerical example and the water‐quality dynamic model for the Nile River) are given to verify the efficiency of the propounded theories. © 2016 Wiley Periodicals, Inc. Complexity 21: 555–578, 2016     

随机环境中的马氏链状态分类

给出了随机环境中马氏链的特征数和状态的定义,讨论了状态间的传递性,自反性,对称性,是经典马氏链相应结果的一般化.并运用位势方法研究了状态间的关系,它们在极限理论的研究中非常有用.     

一类随机环境中的随机游动

研究了在环境平稳遍历时,右半直线上可逗留的随机环境中的随机游动的常返性和非常返性,给出非常返、正常返、零常返的充要条件,并讨论了极限性质.作为推论,给出P独立同分布时的相应结论.     

变系数计量经济学联立模型的局部线性工具向量估计及其性质

联立方程计量经济学模型在经济政策制定、经济结构分析和经济预测方面起着重要作用。本文首次提出了我国宏观经济的一类变系数联立模型,并建立了函数系数的局部线性工具向量估计,同时在时间点列固定设计、经济变量随机设计条件下,研究了估计量的大样本性质。与我国宏观经济经典线性联立模型相比,变系数联立模型拟合效果更优。另外它也有助于克服我国宏观经济数据不多而造成的非参数方法应用困难的现实情况。     

相伴随机变量序列的泛函型几乎处处中心极限定理

对于均值为零的平稳相伴随机变量序列,首先证明了在L(n)=EX_1~2 2 sum from n to j=2 Cov(X_1,X_j)是一个缓变函数的条件下的泛函型几乎处处中心极限定理.另外还给出了正则化部分和函数的对数平均几乎处处收敛性.