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1)  biased stochastic process
有偏随机过程
1.
The concept of time verying Hurst index H(t) is put forward in the biased stochastic process.
有偏随机过程中引入时变指数概念 ,借助小波基能分析局部自相似的特点 ,给出Hurst指数的小波估算公式 ,并证明这种估算式和原指数是相容的 。
2.
The concept of timevarying Hurst index and GFBM model are introduced in stock biased stochastic process.
有偏随机过程中引入时变指数概念和具有局部自相似性的数学模型。
2)  stochastic process
随机过程
1.
A numerical simulation of the track irregularity stochastic process;
轨道不平顺随机过程的数值模拟
2.
Convergence of the sum of a kind of stochastic process;
一类随机过程之和的收敛性
3.
Measurability on Two-Dimensional Stochastic Processes;
两参数随机过程的可测性
3)  stochastic processes
随机过程
1.
Orthogonal expansion of stochastic processes for wind velocity;
脉动风速随机过程的正交展开
2.
The calculation of value at risk when cumulative investment and interest rate is correlative stochastic processes is discussed, and the concept and its calculation of relative value at risk is proposed.
讨论了累积投资和利率为相关随机过程的风险价值,并提出相对风险价值的概念和计算,借助于Monte Carlo模拟分析了累积投资分布参数以及利率参数变化时对于相对风险价值的影响。
3.
A method based on normalized orthogonal bases is proposed to decompose stochastic processes,so as to capture main probabilistic characters of a stochastic process with only a few random variables,and establish a solid foundation for structure stochastic dynamic response and reliability assessment.
建议了一类基于标准正交基的随机过程展开方法。
4)  random process
随机过程
1.
Time-dependent reliability analysis of ship structure based on random process theory;
基于随机过程理论的舰船结构时变可靠性分析
2.
Dynamic reliability analysis and compare of rail based on random process over-crossing theory;
基于随机过程跨越理论的钢轨动力可靠性分析与比较
3.
Evaluation method for project risk based on random process analysis;
基于随机过程分析的项目风险评估方法
5)  random processes
随机过程
1.
Review on simulation methods of random processes in engineering;
工程中随机过程的数值模拟方法及其评述
6)  bounded closed convex set-valued stochastic processes
有界闭凸集值随机过程
1.
In order to study the derivative and integral theories of the set-valued stochastic processes,the mean square derivative of the bounded closed convex set-valued stochastic processes is presented firstly by means of the weak convergence and open notion of sets.
为了研究集值随机过程的微积分理论 ,利用有界闭凸集合弱收敛的性质和集合“开”的概念 ,给出了有界闭凸集值随机过程的均方导数的定义 ,建立了均方导数的若干性质 ,并讨论了集值随机过程均方可导与均方连续的关系。
2.
In order to study the integral and differential theories of the set-valued stochastic processes,the Riemann integral of the bounded closed convex set-valued stochastic processes is firstly given.
为研究集值随机过程的微积分理论 ,首先利用支撑函数定义了二阶矩有界闭凸集值随机过程的均方 Riemann积分 ,其次利用支撑函数以及均方收敛的性质证明了二阶矩有界闭凸集值随机过程的均方 Rie-mann积分的线性性、同数学期望的可交换性等性
补充资料:独立增量随机过程


独立增量随机过程
tochastic process with independent increments

独立增里随机过程「劝刘巨浦c拌.义冠弓初山侧吻创如t加盆,曰n臼lts;cjl抖浦.咸nP0uecc c Ite3洲cltMuM.uP-“P啊eHll,刚』 一种随机过程(s勿比邵石cp~)X(t),对任意自然数”和所有实数O蕊:,<口,簇:2<吞2簇…蕊,。<口。,增量X(乃;)一X(‘J),…,X(刀。)一X(,。)是相互独立随机变量,独立增量随机过程称为齐次的(holll。罗11印us),如果X(:+h)一X(。),0(戊,oO,当t’,t时 p{}Y(t‘)一Y(t)}>。}~0.W汹犯r过程(Wiemr Proo巴粥)和Pb远翔1过程(Po哪npr(x芜‘s)是随机连续的独立增量随机过程的例子(前者的实现以概率1连续,后者的实现是跳跃值等于l的阶梯函数).独立增量随机过程的一个重要例子是稳定过程(见稳定分布(stable面tribution)).随机连续的独立增量随机过程(以概率1)只有第一类间断点.这种过程的值的分布对任意t是无穷可分的(见无穷可分分布(inf谊此ly一山北ible dis州bution))可以用特征函数(chara叱ristic ftmct」on)方法研究独立增量随机过程.关于过程穿越边界的概率以及第一次穿越时间的概率分布等问题,可用所谓因子分解恒等式(fac-tori山tion jdenti往留)来解决.”协月片,巴爹‘人队见随饥双桂L StDchasl」e Process). 刘秀芳译陈培德校
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