2) wide stationary stochastic processes
宽平稳随机过程
3) stationary stochastic processes
平稳随机过程
1.
This paper gives the research of the transformation of stationary stochastic processes passing through the sta- tionary linear dynamics system.
研究了平稳随机过程通过平稳线性动力学系统的变换,通过力学系统、电路系统几个实例的计算,揭示了确定系统输出(响应)的统计特征的一般方法,密切了平稳过程理论与实际的联系。
2.
This paper introduces the differentiation of the stochastic processes under the meaning of mean square limit, and gives the conclusion that the arbitrary rank derivatives of stationary stochastic processes (if they exist) will still be stationary.
介绍了随机过程在均方极限意义下的可微性概念,并论述了平稳随机过程的任意阶导数(如果存在的话)仍然是平稳随机过程这一结论。
4) stationary random process
平稳随机过程
1.
The problem is that because location where vehicles are on the bridge is changeable,so even if random vibration as importation is stationary random process,dynamic response of vehicles is beyond the scope of stationary random process.
由于车辆在桥上的位置是不断变化的,因此,即使作为输入的随机激励是平稳随机过程,车桥的动力响应也超出平稳随机过程的范围,即质量在梁上不断的运动,使系统运动方程组成为一个时变系数的二阶微分方程组,一般只能采用逐步积分的数值方法,也可以用频域法,假定其频率响应函数在瞬间不随时间变化,近似的处理这种时变性问题。
2.
Methods The definition of stationary random processes and joinly stationarity and the method of mathematics induction are used.
目的为了讨论联合平稳随机过程{X(t),t∈T}和{Y(t),t∈T}的导数{X(k)(t),t∈T}与{Y(l)(t),t∈T}(0≤k,l≤n)的联合平稳性。
5) non-stationary stochastic process
非平稳随机过程
1.
Earthquake motions are regarded as the typical non-stationary stochastic processes,and such non-stationary characteristics influence the structural response greatly.
地震动是典型的非平稳随机过程,其非平稳特性对结构响应影响极大。
6) stationary stochastic process
平稳随机过程
1.
In this paper, the state of inspection system which is exploited on integrated circuit chip pin size is analyzed by SAS software based on stationary stochastic process theory The test results show, that inspection results of the system are a stationary stochastic process with ergodicity .
测试 结果表明,整个系统的测量结果是一个具有各态历经性的平稳随机过程,因此,我们利用一段 样本值就能估计整个过程的均值和标准差,从而获得整个过程的性质。
2.
This paper gives a conclusion of the partial derivatives of the covariance function of stationary stochastic process with respect to two independent variables and the proof of the stability of the sum of stationary stochastic process and its derivative,which was extended to the case of the second derivative.
给出平稳过程的自协方差函数对两个变元的偏导数的一个结论,证明了平稳随机过程与其导数之和的平稳性并推广到二阶导数的情形,方法简洁。
3.
Based on the spectral representation theorem of stationary stochastic processes, in this paper, a method is propesed for Monte Carlo simulation of stationary stochastic processes by the fast Hartley transform.
由平稳随机过程谱表示定理导出了平稳随机过程蒙特卡罗模拟的一个快速Hartley变换方法。
补充资料：量子随机过程
量子随机过程
quantum stochastic processes
且子随机过程f印.毗口l动闻脑成k碑0以洲，拐;抽aHTO服ec刃，曲“砒nP0uecc叫[补注】 古典概率和t子概率基础.量子论作为新力学出现，但不久就认识到它也是新的概率论(pro恤bilityt」leory).古典概率和t子概率(qUantum Pm比bility)之间的差别，通常认为事实上是这样的:对于前者，不相容事件的概率相加(pro恤bili6留of恻。int eVellts目d)，而对于后者，不相容事件的振幅相加(姗plit区晚of disjointe祀nts add)，一个事件的振幅(彻叩也理七ofan eVe力t)为一复数，其平方是该事件的概率.更精确的说法是，古典复合概率定理(也印n劝of colrlPositeprobe腼石已) 艺p(al忆)p(b，)一p(a)，(AI) J在量子情况要代之以复合振幅定理(t址幻记m of 00刀。-posite an1Plit波比) 不*‘a，”j，沙‘b，，一沙‘a，;‘A2)其中两个恒等式必须作如下解释:给定振幅妙(川气)，穴幼和相应古典概率p(a}忆)=}妙(。
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