2) Normal stochastic process
正态随机过程
3) complex normal stochastic process
复正态随机过程
4) stochastic process-sliding
随机过程-滑动
5) 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
6) 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。
补充资料：可微随机过程
可微随机过程
stochastic process, differentiaUe
可微随机过程[st佣加stic声伏ess，differen血ue;c几y-，a益H“面npo”ecc月H中中ePe“朋“pyeM“.」 使极限 ，;一-翌上垫竺上卫业立一二，z，、 从二泊△t存在的随机过程(stochastic Process)X(r);X’(t)称为随机过程x(t)的导数(derivative of the stocha-stic process).按照极限解释的不同，可区分为以概率1微分(djflbrentiation侧th pro加bility one)与均方微分(mean一sq场汀e differen石ation).均方可微性的条件可以自然地用相关函数 B(t:，tZ)二EX(tl)X(rZ)来表示，即x‘(t)存在，当且仅当极限 刀’‘(t，，tZ)=一△悠{[B(‘l十A‘:，艺2+△亡2)一刀(忿，+△‘，，‘2)- △rZ~0 一B(t，，t:+△tZ)+B(t，tZ)」/Atl△tZ圣存在.一个有均方导数的随机过程是绝对连续的.更精确地说，对每个t，下式以概率1成立: x(:)一x(:。)+于x，(:)过s，亡)。。. 亡O 一个过程等价于一有连续可微轨道过程的充分条件是其均方导数x’(t)为连续的且以B“(t，，tZ)为其相关函数.对于Gauss过程，这个条件也是必要的.【补注】其他参考文献见随机过程(stochastic pro-cess).潘一民译
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条