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连续随机过程

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New parameter estimation Markov recursive algorithm for continuous stochastic linear system and bilinear system is proposed.

基于小波变换的连续随机线性和双线性系统参数辨识Markov方法分析研究了连续维纳过程在小波变换下的统计特性,给出了维纳过程的离散小波变换系数所构成的离散随机过程的协方差矩阵计算和估计方法,基此提出了线性和双线性连续随机系统参数辨识的Markov估计方法及其递推算法。

But some important events can lead to brusque variations in price. To model this kind of phenomena, we have to introduce discontinuous stochastic process.

然而当一些重大事件发生时,市场价格会发生大的波动,为描述这种现象,这就要求我们引入不连续随机过程

In the Black-Scholes models, the stock price is driven by the Brown motion. It抯a continuous function of time.

在传统B-S模型中,假定资产的价格服从Brown运动,是一个连续随机过程

It is shown that the number of dominant eigenvalues for a continuous random process in with bandwidth is with the aid of the continuous Karhunen-Lo è ve Expansion.

本文利用卡亨南—洛厄维展开对观测时间、带宽为的限带谱连续随机过程进行展开,得到其特征谱的解析表达式,即大特征值个数为。

In this paper,the authors give a strict proof of geometric Brown motion displayed by stock prices using the methods of approximation from discrete process to continuous stochastic process.

通过由一般的离散过程逼近连续随机过程的方法,给予证券价格按有漂移率的几何布朗运动变化的一个严格的证明,并指出了股票价格过程的一般模型

Extremal properties of stationary stochastic sequences and continuous time processes.

平稳随机序列和连续时间过程的极值性质。

In order to improve the validity and reliability of the model, the random state of weapon systems after accomplishing the mission at random time is regarded as a random process, and the computing model of the dependability matrix is established by using Kolmogorov backward and forward equations of the continuous time homogeneous Markov chain. The transfer probability is found by solving the matix differential eguation.

为了提高模型的有效性和可信度,将武器系统在执行任务后任意时刻处于某种状态看作是一个随机过程,应用连续时间齐次马尔可夫桩的柯尔莫哥洛夫向前和向后方程建立可信赖度矩阵计算模型,求解矩阵微分方程得到转移概率。

This project also obtained several limit theorems for some important dependent random variables and stochastic processes, such as the Strassen law of the iterated logarithm for negatively dependent random variables, strong limit theorems for mixing random vectors in Banach spaces, sample path properties for two-parameter fractional Wiener processes, and so on.

随机环境中的随机变量与随机过程的研究在国内外相当活跃,本项目主要研究它们的极限性质,着重研究了随机风景中随机变量与随机过程的极限性质,主要取得了以下几个结果:首先对简单对称的Kesten-Spitzer随机游动在低阶矩的条件下给出了强逼近,大大减弱了前人要求任意阶矩的条件,然后对独立风景中的一般随机变量给出了强逼近的一般性结果,由此导出在风景和随机变量都只具有低阶矩的条件下的独立但不同分布、混合相依变量的强逼近,在只有弱高于二阶矩的条件下得到了重相对数律和弱收敛;给出了连续时间参数的Brown风景中Brown运动和稳定风景中稳定过程的滞后增量和连续模等精确样本轨道性质;同时给出了一些重要的相依随机变量和过程的若干极限定理,如负相关随机变量的Strassen重对数律、抽象空间上混合相依变量的一些强极限定理成立的充分必要条件、两参数分数Wiener过程的样本轨道性质等。

Considering the spatial correlations of interconnect process variations, we modelprocess variations as continual stochastic processes with correlation. For decoupleing thespatial correlation, we express them as an expanded form of independent random variablesby Karhunen-Loeve expansion. Then we use stochastic Galerkin method to solve thedecoupled telegraph equation in the presence of process variations.

考虑互连线工艺变化的空间相关性,将互连线工艺变化建模为具有相关性的连续随机过程;提出采用Karhunen-Loeve展开将该随机过程表示为一组独立随机变量的展开式,从而进行解耦;对解耦后得到的工艺变化下的电报方程,应用随机迦辽金方法求解。

Topics covered include continuous time Markov chains: birth and death processes and queues, introduction to discrete time martingales, Brownian motion and diffusions.

随机过程简介II:包括:连续时间的马尔可夫链:生灭过程和排队过程,离散时间上的鞅,布朗运动和散射。

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