样本函数

  • 网络Sample function
样本函数样本函数
  1. 若单元数目相同,W-S法综合的方向图更逼近样本函数,且天线的波瓣较窄,增益较高。

    If the same number of elements is used , the synthesized pattern will have better approach to the sample function , narrower beamwidth , and higher gain .

  2. 根据秦沈客运专线高速试验段轨检车资料,采用ARMA时间序列模型模拟了高速铁路轨道不平顺随机样本函数;

    With the data obtained from track geometry inspection car on Qinhuangdao-Shenyang special line for passenger transport and ARMA time series model , the sample function of high-speed railway track random geometric irregularity are simulated .

  3. 广义Poisson单的跳线和样本函数的结构

    Jumping Lines and Structure of Sample Functions for Generalized Poisson Sheet

  4. 这个类包含具有右连续样本函数的Feller过程。

    The kind includes Feller processes with right continuous sample functions .

  5. 本文在模糊变量和动态模糊集合的基础上定义了模糊过程、构造了它的F样本函数,然后用F样本函数定义了模糊过程的a。

    In this paper , based on the fuzzy variable and dynamic fuzzy set , a fuzzy process is defined and its F-sample functions are constructed . Then , by means of F-sample functions , a kind of a.

  6. 由于PBD算法需要在估计样本函数的同时估计PSF的参数,一般采用的PSF的模型较为复杂,计算量大,收敛慢;

    The PBD algorithm needed to simultaneously estimate the specimen function and the parameters of the PSF , while the PSF model was complicated , needed a large number of computation and converged slowly .

  7. 本文给出的W&S综合法,利用样本函数的性质,对Woodward法进行了改进,用较少的单元就可以综合出相同效果的方向图。

    Based on the property of sample function , the W-S synthesis method is developed from Woodward method . It can be to synthesize the pattern with less elements .

  8. 利用结构反应的头四阶矩,基于Winterstein变换,模拟非高斯荷载作用下结构的反应过程,并由结构反应过程的样本函数,建立了结构首次失效时间分析的模拟方法。

    Based on the first to fourth moments of structural random responses and Winterstein transformation , structural responses under Non-Gaussian load are simulated . Using sample functions of structural responses , a Mont Carlo simulation method for the first failure time of a structure excited by Non-Gaussian load is presented .

  9. 集值随机过程的样本函数连续性

    On the Continuity of Sample Function for Set valued Stochastic Process

  10. 一定条件下样本函数极值的重采样方法

    Resampling Methods for the Extrema of Certain Conditional Sample Functions

  11. 关于两指标随机过程样本函数的连续性

    On the Continuity of Sample Function of Two-Parameter Stochastic Process

  12. 样本函数条件极值的渐近性质

    Asymptotic Properties of Extrema of Certain Conditional Sample Functions

  13. 马氏过程的某些样本函数性质

    Some properties of sample functions of Markov processes

  14. 强平稳过程样本函数的连续性

    Continuity of Sample Function of Strong Stationary Process

  15. 样本函数的跳跃与连续性

    Bound and Continuous Qualities of Function Sample

  16. 宽过去马氏过程的样本函数连续性

    Sample Path Continuity of Wide-Past Markov Processes

  17. 本文讨论了两指标随机过程样本函数连续性的另两种形式。

    In this paper , we discuss two new conditions for the continuity of sample function of two-parameter stochastic process .

  18. 同时给出了加在链和过程样本函数上的充分条件。

    Moreover , some sufficient conditions on the jointly Markov chains and sample function of the jointly Markov chains are given .

  19. 设ξ(t)(t≥0)是一严平稳过程,具有连续的样本函数,且ξ(t)的分布函数是连续的。

    Let ( t ) ( t > 0 ) be a strictly stationary . process with continuous sample functions , and the d.

  20. 本文把标值随机点过程的理论移植到金融计量经济学中,通过定义表征价格运动的标值随机点过程强度计算公式,导出了甚高频金融交易数据的样本函数密度公式,以及最大似然估计方程式。

    This paper transplants marked point process theory to financial econometrics to analyze ultra-high-frequency data , derives sample function density and its maximum likelihood estimating formulation .

  21. 结果发现随机行走价格样本函数中阶段性趋势普遍存在,移动平均线法对每一模拟样本函数均能获得高额回报。

    The results are : it is very common that there are trends in Monte Carlo random walk we can get excessive return with moving average method .

  22. 根据我国干线铁路轨道谱,采用三角级数法模拟出干线铁路和准高速铁路轨道不平顺的样本函数;

    By means of trigonometrical progression method and the mainline track spectrum , the sample function of the Chinese mainline railway track random geometric irregularity is simulated .

  23. 本文讨论强平稳过程的样本函数,对其连续性提出了四个充分条件,并且在[2]的基础上对独立增量的情形给出一个充分条件。

    In this paper we give four sufficient conditions about the continuity of sample function of strong stationary process . A new sufficient condition is given under the condition of independent increment process .

  24. 证明了随机目标函数的每个样本函数是连续可微的凸函数,给出了选择随机最优场址的算法,并证明了其收敛性。

    It is proved that the sample function of random objective function is continuous differentiable and convex . The algorithm for random continuous type optimal location is provided and its convergence is proved .

  25. 对一类阶梯过程的模型进行定义,提出单位时间内的平均跳跃次数和跳跃度分布函数,给出产生该阶梯过程的样本函数。

    A model of step process was defined , and avenue jump frequency and distributed function of jumping degree were given in this paper , and the sample function of step process was offered as well .

  26. 本文对一定条件下样本函数极值的重采样方法进行了研究,给出了γ~2估计的几种方法,包括减-d折刀法、减-1折刀法和自助法;

    In this paper some resampling methods for the extrema of certain conditional functions are examined . Some methods of estimator of γ ~ 2 are offered , including delete - d jackknife , delete-1 jackknife and bootstrap method .

  27. 假定在设计基准期[0,T]内结构应力为复合指数几何过程,给出应力随机过程的样本函数的最大值分布,并获得其近似表达式。

    Considering structural stress during the standard period of the design of obeying compound exponential geometric process , give the formular of probability distribution of maximum of stress obey compound exponential geometric process S ( t ) and its approximate formular .

  28. 在第二章中,建立了具有离散参数的马氏环境中马氏链函数的极限定理,并给出了加在双链和过程样本函数上的一些充分条件。

    In second chapter , some limit theorems for function of countable Markov chains in Markovian environments were obtained , at the same time , some sufficient conditions on the jointly Markov chains and sample function of the jointly Markov chains were given .

  29. 在此基础上,研究了具有离散参量的马氏环境中马氏链函数的强大数定律,并且给出了直接加于链和过程样本函数上的充分条件。

    On this base , a strong law of large numbers for function of Markov chains in Markovian environments with discrete parameter is discussed , and some sufficient conditions on the jointly Markov chains and sample function of the jointly Markov chains are given .

  30. 距离检验方法可以根据一个实测样本函数或多个实测样本函数对动态仿真结果进行高置信度的检验,并且对时间序列没有任何限制,即对平稳和非平稳的时间序列均适用。

    By the method , dynamic simulation results can be tested at a high confidence level according to one measured sample function or multiple measured sample functions . This method has no limitation for time series , namely suitable for the stationary and the non-stationary time series .