扩散过程关于（r,p）—容度的大偏差

本文证明扩散过程关于（ｒ，ｐ）－容度服从大偏差原理，作为此结果的一个应用，我们证明扩散过程的拟泛函重对数律成立。     

二维扩散过程保序耦合的存在性

本文研究扩散过程轨道的保序时，对二维非退化扩散过程，我们证明其保序耦合存在，同时构造出一类保序算子。     

紧流形上非退化扩散过程的成功耦合

本文构造了紧连通流形上非退化扩散过程的一些耦合，并使用随机分析的方法证明这些耦合是成功的，进一步地，耦合时间一阶矩有限。最后，我们使用耦合方法研究了扩散过程依全变差范数的收敛速度。     

扩散过程在Hlder范数下的大偏差(英文)

本文利用一种推广的收缩原理，证明扩散过程在Ｈｌｄｅｒ范数下大偏差原理仍成立     

扩散过程在Holder范数下的大偏差

本文利用一种推广的收缩原理，证明扩散过程在Ｈｏｌｄｅｒ范数不大偏差原理仍成立。     

暂留对称扩散过程全占据时的大偏差

本文讨论暂留对称扩散过程的全占据时的大偏差．我们证明在一致椭圆条件下,暂留对称扩散过程的全占据时满足大偏差原理．     

多物种无穷维反应扩散过程的唯一性

本文利用鞅方法,证明多物种无穷维反应扩散过程的唯一性。     

有限维Brusseltor模型的正常返性

本文证明了多物种反应扩散过程的一种基本模型－Ｂｒｕｓｓｅｌｔｏｒ模型在有限维情形下总是正常返的，因而是遍历的，事实上还是指数遍历的。     

Markov切换扩散过程的几乎处处渐近稳定性

本文研究一类Markov切换扩散过程的样本轨道长时间行为,分几类情形讨论其几乎处处渐近稳定性.对于Markov链状态空间是有限的这类过程的稳定性,应用Perron-Frobenius定理证明;对于可逆的Markov链且其状态空间是有限的这类过程的稳定性,应用主特征值方法证明;对于Markov链状态空间是可数的这类过程的稳定性,应用有限划分技巧及M-矩阵方法证明.每一种情形,相应的例子给出了说明.进一步,使用得到的理论,对线性Markov切换扩散过程的反馈控制问题进行讨论.     

基于谱隙的依全变差指数式收敛速度估计

利用与谱隙作比较的手法，本文研究可逆马氏过程依全变差的指数式收敛速度．我们证明在相当一般的情况下，只要对初分布略加限制，则此速度以谱隙为下界．进而，对于紧空间情形或生灭过程或半直线上的扩散，我们证得此速度等于谱隙．     

基于遗传算法的附随扩散模型的构建及实证研究

论文研究了具有附随扩散关系的产品扩散特点,以Bass模型为理论基础,构建了附随扩散模型,然后以移动上网用户附随移动用户扩散的实例为研究对象,建立了移动上网附随扩散模型,并采用遗传算法估算模型参数,对今后几年移动上网用户的扩散规律进行了预测。最后,将附随扩散模型的研究结果与采用传统Bass模型、Logistic模聊的结果进行了对比,得出了附随扩散模型拟合和预测效果更好的结论。     

扩散速度与组元的质量守恒方程

在混合物流动中,某组元i的质量迁移速度(绝对速度)等于对流速度(牵连速度)与扩散速度(相对速度)之和.扩散速度——以及扩散系数——依对流速度取法之不同而不同.在湍流中,组元i的质量迁移速度是(?)(质量加权的时间平均速度).扩散速度((?)-a)是由湍流扩散速度(?)和分子扩散速度v_1-a所组成((?)是组元i的时平均速度,a是某种取法的对流速度).因此,湍流扩散速度与对流速度的取法无关.组元i的质量守恒方程,其右端的扩散须依其左端对流速度取法之不同而不同.在湍流情况下,它可能没有扩散项,或只有湍流扩散项,或既有湍流扩散项又有分子扩散项,如果我们取(?),或(?),或任何其它速度作为对流速度的话.在层流中会遇到只有分子扩散项而无湍流扩散项的例子.分子扩散总是依赖于对流速度的选取.与混合气体情况不同,在二相流中.分子扩散项的重要性相当于、或甚至超过湍流扩散项.     

Wavelet estimation of the diffusion coefficient in time dependent diffusion models

The estimation problem for diffusion coefficients in diffusion processes has been studied in many papers,where the diffusion coefficient function is assumed to be a 1-dimensional bounded Lipschitzian function of the state or the time only.There is no previous work for the nonparametric estimation of time-dependent diffusion models where the diffusion coefficient depends on both the state and the time.This paper introduces and studies a wavelet estimation of the time-dependent diffusion coefficient under a more general assumption that the diffusion coefficient is a linear growth Lipschitz function.Using the properties of martingale,we translate the problems in diffusion into the nonparametric regression setting and give the L~r convergence rate.A strong consistency of the estimate is established.With this result one can estimate the time-dependent diffusion coefficient using the same structure of the wavelet estimators under any equivalent probability measure.For example, in finance,the wavelet estimator is strongly consistent under the market probability measure as well as the risk neutral probability measure.     

Time/depth dependent diffusion and chemical reaction model of chloride transportation in concrete

This study focuses on the physical and chemical processes that control the transport of chloride ions into concrete structures. An analytical solution of a diffusion reaction model is presented for determining the time/depth dependent chloride diffusivities considering both diffusion process and binding mechanism of chloride occur simultaneously. The diffusion-reaction model, which is based on the Fick’s second law of diffusion and a mathematical formulation for an irreversible first-order chemical reaction, is used to precisely describe the diffusion mechanism of chloride diffusion process. When the chemical reaction is considered, the free chloride concentration is slowly reduced since some of the free chloride ions have reacted with cement paste such that the diffusion coefficient is also reduced simultaneously. The diffusion-reaction model predicts a longer service life than the total and free chloride diffusion models that do not consider the effect of the chemical reaction during the chloride diffusion process.     

Prediction and Conditional Simulation of a 2D Lognormal Diffusion Random Field

This paper describes techniques for estimation, prediction and conditional simulation of two-parameter lognormal diffusion random fields which are diffusions on each coordinate and satisfy a particular Markov property. The estimates of the drift and diffusion coefficients, which characterize the lognormal diffusion random field under certain conditions, are used for obtaining kriging predictors. The conditional simulations are obtained using the estimates of the drift and diffusion coefficients, kriging prediction and unconditional simulation for the lognormal diffusion random field.      

Research on competition diffusion of the multiple-advanced manufacturing mode in a cluster environment

This paper deals with competition diffusion of multiple-advanced manufacturing modes in a cluster environment, to reveal the competition diffusion rules of the advanced manufacturing mode. First, the influencing factors on advanced manufacturing mode diffusion in a cluster environment are analysed. Second, the diffusion properties and the diffusion mechanism are analysed, and the competition diffusion model of multiple-modes is established. Third, the model is analysed and the qualitative results are presented. Finally, the application of the diffusion model is exemplified and simulated (by matlab 7.1), producing results that are consistent with qualitative analysis that also verifies the correctness of the model. In addition, the influence of the cluster environment is discussed. The diffusion model helps enterprises understand the diffusion rules of the advanced manufacturing modes and provides a decision-making basis for enterprises and government.     

Strong Stationary Duality for Diffusion Processes

We develop the theory of strong stationary duality for diffusion processes on compact intervals. We analytically derive the generator and boundary behavior of the dual process and recover a central tenet of the classical Markov chain theory in the diffusion setting by linking the separation distance in the primal diffusion to the absorption time in the dual diffusion. We also exhibit our strong stationary dual as the natural limiting process of the strong stationary dual sequence of a well-chosen sequence of approximating birth-and-death Markov chains, allowing for simultaneous numerical simulations of our primal and dual diffusion processes. Lastly, we show how our new definition of diffusion duality allows the spectral theory of cutoff phenomena to extend naturally from birth-and-death Markov chains to the present diffusion context.     

Revisiting key schedule’s diffusion in relation with round function’s diffusion

We study the weakness of key schedules from an observation: many existing attacks use the fact that the key schedules poorly distribute key bits in the diffusion path of round functions. This reminds us of the importance of the diffusion’s relation between key schedules and round functions. We present new cryptanalysis results by exploring such diffusion relation and propose a new criterion for necessary key schedule diffusion. We discuss potential attacks and summarize the causes for key schedules without satisfying this criterion. One major cause is that overlapping between the diffusion of key schedules and round functions leads to information leakage of key bits. Finally, a measure to estimate our criterion for recursive key schedules is presented. Today designing key schedule still lacks practical and necessary principles. For a practical key schedule with limited diffusion, our work adds more insight to its requirements and helps to maximize the security level.     

Diffusion maps tailored to arbitrary non-degenerate Itô processes

We present two generalizations of the popular diffusion maps algorithm. The first generalization replaces the drift term in diffusion maps, which is the gradient of the sampling density, with the gradient of an arbitrary density of interest which is known up to a normalization constant. The second generalization allows for a diffusion map type approximation of the forward and backward generators of general Itô diffusions with given drift and diffusion coefficients. We use the local kernels introduced by Berry and Sauer, but allow for arbitrary sampling densities. We provide numerical illustrations to demonstrate that this opens up many new applications for diffusion maps as a tool to organize point cloud data, including biased or corrupted samples, dimension reduction for dynamical systems, detection of almost invariant regions in flow fields, and importance sampling.     

基于社会网络结构的创新扩散动力机制及其仿真研究

随着社会资本的大量涌入,创新扩散逐渐受到社会网络关系的影响。在分析了创新扩散机理的基础上,构建了基于不同拓扑结构的创新扩散演化动力模型。将信息获取、领导者创新能力及机会利益作为创新扩散的动力因子。通过利用复杂网络的演化博弈仿真分析,揭示了小世界、无标度等不同网络拓扑结构下,创新技术的扩散情况。仿真结果表明:在网络结构相同的情况下,信息获取对创新扩散的影响较大;在动力因子设定相同的情况下,网络主体连接越规则,创新扩散越充分。