一类连续半鞅型随机微分方程解的随机稳定性

本文利用Ｌｙａｐｕｎｏｖ函数方法，讨论了时齐Ｄｏｌｅａｎｓ－Ｄａｄｅｒ－Ｐｒｏｔｔｅｒ方程ｄＸ＿ｔ＝σ（Ｘ＿ｔ）ｄＭ＿ｔ＝ｂ（Ｘ＿ｔ）ｄＡ＿ｔ＋（（Ｍ＿ｔ）为连续局部平方可积鞅；（Ａ＿ｔ）为连续有限变差过程）平凡解的随机稳定性。本文建立了随机稳定性的判定定理并给出了相应的Ｌｙａｐｕｎｏｖ函数的一种具体形式。     

保险公司每期总准备金计算

本在保险公司是风险中性的情况下，讨论了在投资影响下的每期总准备金计算问题．通过建立它应满足的线性倒向随机微分方程，得到它在投资影响下的计算公式．     

Neutral stochastic functional differential equations with additive perturbations

The paper deals with the solution to the neutral stochastic functional differential equation whose coefficients depend on small perturbations, by comparing it with the solution to the corresponding unperturbed equation of the equal type. We give conditions under which these solutions are close in the (2m)th mean, on finite time-intervals and on intervals whose length tends to infinity as small perturbations tend to zero.     

Study of an S-I epidemic model with nonlinear incidence rate: Discrete and stochastic version

Discrete and stochastic version of a susceptible-infective model system with nonlinear incidence rate is investigated. We observe that the discrete system converges to a unique equilibrium point for certain effective transmission rate of the disease and beyond which stability of the system is disturbed. Stochastic analysis suggests that the model system is globally asymptotically stable in probability for certain strengths of white noise. Numerical simulations are also performed to validate the results.     

投资影响下的再保险策略

本文研究了投资影响下的再保险策略,利用有关的线性正倒向随机微分方程,获得投资影响下再保险的自留比例或自留额的计算式子.     

A filtering problem with a small nonlinear term

In this paper, we consider a filtering problem where the signal X _t satisfies a slightly nonlinear stochastic differential equation and we want to obtain estimates of X _t. To this end, we decompose the nonlinearity with two techniques—a deterministic one and a stochastic one—and this leads us to two sequences of estimates which can be computed by solving finite dimensional equations. We want to compare their performances: we solve this problem in most cases if we restrict ourselves to sufficiently small times t and we give conditions which permit to conclude also for larger times     

Kalman-Bucy filtering equations of forward and backward stochastic systems and applications to recursive optimal control problems

This paper is concerned with Kalman-Bucy filtering problems of a forward and backward stochastic system which is a Hamiltonian system arising from a stochastic optimal control problem. There are two main contributions worthy pointing out. One is that we obtain the Kalman-Bucy filtering equation of a forward and backward stochastic system and study a kind of stability of the aforementioned filtering equation. The other is that we develop a backward separation technique, which is different to Wonham's separation theorem, to study a partially observed recursive optimal control problem. This new technique can also cover some more general situation such as a partially observed linear quadratic non-zero sum differential game problem is solved by it. We also give a simple formula to estimate the information value which is the difference of the optimal cost functionals between the partial and the full observable information cases.     

随机泛函微分方程的渐近稳定性

应用多个Liapunov函数讨论了随机泛函微分方程解的渐近行为,建立了确定这种方程解的极限位置的充分条件,并且从这些条件得到了随机泛函微分方程渐近稳定性的有效判据,使实际应用中构造Liapunov函数更为方便．同时也说明了该结果包含了经典的随机泛函微分方程稳定性结果为其特殊情况．最后给出的结果在随机Hopfield神经网络中的应用．     

On the integrability of the (1+1)-dimensional and (2+1)-dimensional Ito equations

Under investigation in this paper are the (1+1)-dimensional and (2+1)-dimensional Ito equations. With the help of the Bell polynomials method, Hirota bilinear method and symbolic computation, the bilinear representations, N-soliton solutions, bilinear Bäcklund transformations and Lax pairs of these two equations are obtained, respectively. In particular, we obtain a new bilinear form and N-soliton solutions of the (2+1)-dimensional Ito equation. The bilinear Bäcklund transformation and Lax pair of the (2+1)-dimensional Ito equation are also obtained for the first time. Copyright © 2014 John Wiley & Sons, Ltd.     

随机Cahn-Hilliard方程的一种差分逼近

Stochastic Cahn-Hilliard equation is an equation of the field theory for solving the Non-equilibrium dynamics problem in a weak state and is a case of nonlinear Langevin equation.In this paper,using the ackward difference method(BDM),a numerical solution of the stochastic C-H equation is proposed and using the Ito formula,probability and the martingale theory,the convergence of the numerical process is proved in the meaning of mean square.     

A note on Jensen’s inequality for BSDEs

Under the Lipschitz assumption and square integrable assumption on g, Jiang proved that Jensen＇s inequality for BSDEs with generator g holds in general if and only if g is independent of y, g is super homogenous in z and g（t, 0） = 0, a.s., a.e.. In this paper, based on Jiang＇s results, under the same assumptions as Jiang＇s, we investigate the necessary and sufficient condition on g under which Jensen＇s inequality for BSDEs with generator g holds for some specific convex functions, which generalizes some known results on Jensen＇s inequality for BSDEs.     

推广的Bessel过程的L~p估计

随机微分方程dX_t=(δf~2(t)-h(t)X_t)dt+2f(t) │X_t│～(1/2)dBt,(X_0=x,δ>0)的解X_t是一种推广的δ(δ>0)维Bessel过程.文章对于任意停时τ给出了‖sup0≤t≤τη(t)X_t‖p的L~p估计,其中η:R_+→R_+是一个R+上的可微函数,而且满足微分方程dη/dt-h(t)η=-η~2f~2(t),η(0)=1.     

A link of stochastic differential equations to nonlinear parabolic equations

Using Girsanov transformation,we derive a new link from stochastic differential equations of Markovian type to nonlinear parabolic equations of Burgers-KPZ type,in such a manner that the obtained BurgersKPZ equation characterizes the path-independence property of the density process of Girsanov transformation for the stochastic differential equation.Our assertion also holds for SDEs on a connected differential manifold.     

On the solution of stochastic ordinary differential equations via small delays

dx(t)=g(x{t))dW(t) is proved using an approximating sequence of stochastic delay equationsGeneralizations of the approximation scheme are indicated for the Stratonovich case and when the Brownian motion W is replaced by a continuous semi-martingale.     

求解阵列天线自适应滤波问题的一种调比随机逼近算法

提出了求解阵列天线自适应滤波问题的一种调比随机逼近算法.每一步迭代中,算法选取调比的带噪负梯度方向作为新的迭代方向.相比已有的其他随机逼近算法,这个算法不需要调整稳定性常数,在一定程度上解决了稳定性常数选取难的问题.数值仿真实验表明,算法优于已有的滤波算法,且比经典Robbins-Monro （RM）算法具有更好的稳定性.     

Stochastic methods for Dirichlet problems

Using an equivalent expression for solutions of second order Dirichlet problems in terms of Ito type stochastic differential equations, we develop a numerical solution method for Dirichlet boundary value problems. It is possible with this idea to solve for solution values of a partial differential equation at isolated points without having to construct any kind of mesh and without knowing approximations for the solution at any other points. Our method is similar to a recently published approach, but differs primarily in the handling of the boundary. Some numerical examples are presented, applying these techniques to model Laplace and Poisson equations on the unit disk. Visiting Professor, Universidad de Salamanca.     

基于投资的再保险定价模型

从系统的观点出发,把公司的赔付情况与投资收益相接合,对比例再保险与超额损失再保险,建立了在投资影响下的带跳的再保险模型,给出了基于投资的再保险定价公式,为公司厘订再保险费提供了新的方法.