缺初值估计的最优性

当随机能观测条件成立时,在文献[1—3]中分别对离散时间和连续时间系统用极限过渡的办法得到了对状态和初值的无偏估计——缺初值估计,同时得到了估计误差的协方差阵.本文证明缺初值估计就是不用初始统计特性的线性无偏最小方差估计.熟知的Gauss估计就是对离散时间量测噪声非退化这一特殊情形的缺初值估计.     

最小方羞无偏线性内插与外推

<正> 对线性随机系统,当初值统计特性未知,并且量测噪声协方差阵可能退化时,我们在[1]中得到了对状态及初值的最小方差无偏线性估计.本文将对连续时间和离散时间系统分别得到最小方差无偏线性內插与外推公式.     

连续时间系统的随机能观测性和缺初值估计

本文对连续时间线性随机系统给出了判别随机能观测的充分必要条件.如果系统退化为确定性系统,这个条件就成为判别系统完全能观测的条件.当系统随机能观测时,本文还讨论了未知初值统计特性时的状态和初值的估计问题。     

随机Motsch-Tadmor模型的集群行为研究

将乘性白噪声作为系统的扰动因素,研究随机环境下的Motsch-Tadmor模型的集群行为.在由非对称耦合网络连接各粒子的系统中,给出随机系统发生集群行为的定义,通过对噪声强度和初值的控制使得系统能够以指数收敛的速度达到稳定的平衡状态,并得到发生集群行为的充分条件.     

随机动力学:内源与外源噪声的数学模型及其应用

复杂系统与过程的数学建模需要用随机动力学(stochastic dynamics)的思想和方法.随机动力学的理论有着两种不同的数学表述:随机过程(stochastic processes)和随机动力系统(random dynamical systems).后者是比前者更为精细的数学模型,它不但给出对应于每一个初值的随机过程,还全面地描述不同初值的多条随机轨道如何同时随时间变化.前者恰恰表述了有内在随机性的个体的运动,而后者则反映了多个相同的确定性个体同时经历同一个随机环境.本文称这两种情形为内源噪声和外源噪声.两者都在化学和生物学中有广泛的应用.近年来兴起的以图G(V,E)为基础的概率布尔网络正是一类以{0,1}~V为状态空间的随机动力系统(RDS).本文介绍有关离散时间离散空间的RDS,同时也给出一个它在统计推断隐Markov模型的收敛速率估算中的应用.     

BSDE在跳框架下的风险敏感控制问题中的应用

本文研究了由带跳的随机微分方程驱动的风险敏感控制问题.利用测度变换和带跳的二次增长的倒向随机微分方程,证明了此问题最优控制的存在性,并通过相应倒向随机微分方程解的初值给出了此问题的值函数.     

加性二值噪声激励下Duffing系统的随机分岔

研究了Duffing系统在加性二值噪声作用下的随机分岔现象.首先,根据二值噪声的统计特性,推导得到二值噪声状态间的跃迁概率,据此对二值噪声进行了数值模拟.其次,利用四阶Runge-Kutta(龙格-库塔)数值算法得到该系统位移和速率的稳态联合概率密度及位移的稳态概率密度.然后,通过对位移稳态概率密度单双峰结构变化的研究,发现加性二值噪声的状态和强度能够诱导系统产生随机分岔现象.最后,观察到随着系统非对称参数的逐渐变化,系统同样产生了随机分岔现象.     

加性和乘性噪声对随机偏微分方程的激励性（英文）

本文研究加性噪声和乘性噪声对一类随机偏微分方程激励性问题.利用It?公式和能量估计方法方法,得出在两种不同噪声下,相对应的随机偏微分方程噪声激励指标不同.从而从这个角度来看,加性噪声与乘性噪声对随机偏微分方程的影响是不一样的.     

广义算子意义下的量子随机微分方程

本文研究广义算子及其Wick积意义下的最子随机微分方程。主要结果为：建立了解的存在唯一性定理；证明了解的连续性及解对初值的连续依赖性，本文给出了两个例子。     

海洋噪声随机场时空局部谱的展开

本文对海洋噪声源进行随机平面波展开,研究其在分层不均匀媒质中传播所形成的噪声场的精细时空统计结构,并讨论了噪声场时空谱展开性质,引进了“噪声场时空局部谱”的概念。文中给出了噪声场时空局部谱函数与海洋噪声源特性以及传播条件之间物理意义的明晰普遍关系式,据此又详尽地讨论了海洋噪声场时空相关函数和噪声场方向性函数及其相互关系,最后论证了在浅海声速负梯度、浅海负跃层和深海声道的条件下存在着意义重大的“低噪声信道”。     

Stochastic control stabilizing unstable or chaotic maps

This paper considers a stabilizing stochastic control which can be applied to a variety of unstable and even chaotic maps. Compared to previous methods introducing control by noise, we relax assumptions on the class of maps, as well as consider a wider range of parameters for the same maps. This approach allows to stabilize unstable and chaotic maps by noise. The interplay between the map properties and the allowed neighbourhood where a solution can start to be stabilized is explored: as instability of the original map increases, the interval of allowed initial conditions narrows. A directed stochastic control aiming at getting to the target neighbourhood almost sure is combined with a controlling noise. Simulations illustrate that for a variety of problems, an appropriate bounded noise can stabilize an unstable positive equilibrium, without a limitation on the initial value.     

A new probabilistic fuzzy model: Fuzzification–Maximization (FM) approach

Over the past few decades, fuzzy logic systems have been used for nonlinear modeling and approximation in many fields ranging from engineering to science. In this paper, a new fuzzy model is developed from the probabilistic and statistical point of view. The proposed model decomposes the input–output characteristics into noise-free part and probabilistic noise part and identifies them simultaneously. The noise-free model recovers the nominal input–output characteristics of the target system and the noise model gives approximation to the probabilistic nature of the added noise. To identify the two submodels simultaneously, we propose the Fuzzification–Maximization (FM). Finally, some simulations are conducted and the effectiveness of the proposed method is demonstrated through the comparison with the previous methods.     

Study and modelling of two apple quality attributes: the soluble solids content and the firmness

Recently, the basic dynamics of fruit characteristics have been modelled using a stochastic approach. The time evolution of apple quality attributes was represented by means of a system of differential equations in which the initial conditions and model parameters are both random. In this work, a complete study of two apple quality attributes, the soluble solids content and the firmness, is carried out. For each of these characteristics, the system of differential equations is linear and the state variables and the parameters are represented as random variables with their statistical properties (mean values, variances, covariances, joint probability density function) known at the initial time. The dynamic behaviour of these statistical properties is analysed. The variance propagation algorithm is used to obtain an analytical expression of the dynamic behaviour of the mean value, the variance, the covariance and the probability density function. A Monte Carlo method and the Latin hypercube method were developed to obtain a numerical expression of the dynamic behaviour of these statistical quantities and particularly to follow the time evolution of joint probability density function which represents one but the best mean to characterize random phenomena linked with fruit quality attributes.     

Well-Posedness and Asymptotic Behaviors for a Predator-Prey System with Lévy Noise

In this paper, well-posedness and asymptotic behaviors for a predator-prey system with Lévy noise are studied by using stochastic analytical techniques. Firstly, the existence and uniqueness of positive global solution with positive initial value is proved. Then, stochastic permanence for the system is investigated. Finally, persistence in mean and extinction for the system are discussed and some numerical simulations are provided to support our results.     

The problem of computing the value of a differential game for a positional functional

A dynamical system driven by controls and uncontrollable noise is considered in a game-theoretic setting [1–8]. The problem of feedback control in which the performance index is a positional functional of the motion of the system [8–11] is investigated. On the assumption that the structure of the functional satisfies reasonably general conditions, a procedure is proposed for computing the value of the corresponding differential game. Irrespective of the number of dimensions in the initial problem, as dictated by the structure of the performance index, the proposed procedure reduces to the problem of the successive construction of the upper convex hulls of certain auxiliary functions in domains whose dimension does not exceed that of the phase vector of the system.     

证券价格长期波动控制系统的最优控制策略

探讨证券价格长期波动控制系统的最优控制问题.建立了在有效市场条件下证券价格长期波动的控制系统模型.为了使证券价格和内在价值按照人们预期的目标变化,探讨了对它们服从的系统采用经典信息结构下的随机最优控制策略问题.设计了使系统的输出跟踪证券内在价值的估计值,同时使调节控制的幅度尽可能小的性能指标,给出了最优控制策略的求解公式和计算过程,并给出了考虑系统性能的计算过程,对相应结果进行了分析.主要结论是:当价值对价格的均衡回归调整不足,或投资者对前期价值的增值预期乐观时,最优控制策略所起的作用在加强;而当价值对价格的均衡回归调整过度,或投资者对前期价值的增值预期悲观时,最优控制策略所起的作用在减弱.这些结果可以为完善证券市场和上市公司的监管提供理论依据     

Stability,coherent spiking and synchronization in noisy excitable systems with coupling and internal delays

We study the onset and the adjustment of different oscillatory modes in a system of excitable units subjected to two forms of noise and delays cast as external or internal according to whether they are associated with inter- or intra-unit activity. Conditions for stability of a single unit are derived in case of the linearized perturbed system, whereas the interplay of noise and internal delay in shaping the oscillatory motion is analyzed by the method of statistical linearization. It is demonstrated that the internal delay, as well as its coaction with external noise, drive the unit away from the bifurcation controlled by the excitability parameter. For the pair of interacting units, it is shown that the external/internal character of noise primarily influences frequency synchronization and the competition between the noise-induced and delay-driven oscillatory modes, while coherence of firing and phase synchronization substantially depend on internal delay. Some of the important effects include: (i) loss of frequency synchronization under external noise; (ii) existence of characteristic regimes of entrainment, where under variation of coupling delay, the optimized unit (noise intensity fixed at resonant value) may be controlled by the adjustable unit (variable noise) and vice versa, or both units may become adjusted to coupling delay; (iii) phase synchronization achieved both for noise-induced and delay-driven modes.     

On Generalized Regular Stochastic Differential Delay Systems with Time Invariant Coefficients

Abstract

In this article, we consider the generalized linear regular stochastic differential delay system with constant coefficients and two simultaneous external differentiable and non differentiable perturbations. These kinds of systems are inherent in many application fields; among them we mention fluid dynamics, the modeling of multi body mechanisms, finance and the problem of protein folding. Using the regular Matrix Pencil theory, we decompose it into two subsystems, whose solutions are obtained as generalized processes (in the sense of distributions). Moreover, the form of the initial function is given, so the corresponding initial value problem is uniquely solvable. Finally, two illustrative applications are presented using white noise and fractional white noise, respectively.     

Natural gradient algorithm for stochastic distribution systems with output feedback

In this paper, we use natural gradient algorithm to control the shape of the conditional output probability density function for the stochastic distribution systems from the viewpoint of information geometry. The considered system here is of multi-input and single output with an output feedback and a stochastic noise. Based on the assumption that the probability density function of the stochastic noise is known, we obtain the conditional output probability density function whose shape is only determined by the control input vector under the condition that the output feedback is known at any sample time. The set of all the conditional output probability density functions forms a statistical manifold (M), and the control input vector and the output feedback are considered as the coordinate system. The Kullback divergence acts as the distance between the conditional output probability density function and the target probability density function. Thus, an iterative formula for the control input vector is proposed in the sense of information geometry. Meanwhile, we consider the convergence of the presented algorithm. At last, an illustrative example is utilized to demonstrate the effectiveness of the algorithm.