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strong approximation
相关语句
  强逼近
     STRONG APPROXIMATION OF CONJUGATE BOCHNER RIESZ MEANS OF F AT CRITICAL INDEX ON H~P(T)(1/2
     临界阶共轭Bochner-Riesz平均在H~p(T)(1/2强逼近
短句来源
     STRONG APPROXIMATION OF RANDOM WEIGHTING M-ESTIMATES IN SEMIPARAMETRIC REGRESSION MODEL
     半参数回归模型中随机加权M估计的强逼近
短句来源
     Strong Approximation And Weak Convergence for N-union Station Fork-Join Queueing Network
     N台并联Fork-Join排队网络的弱收敛与强逼近
短句来源
     Strong Approximation and Improved Erds Rényi Laws of Sums for Independent Non-Identically Distributed Random Variables
     独立随机变量部分和的强逼近与广义Erds-Rényi大数律
短句来源
     STRONG APPROXIMATION FOR A FORK-JOIN QUEUING NETWORK
     一类Fork-Join排队网络的强逼近
短句来源
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  “strong approximation”译为未确定词的双语例句
     STRONG APPROXIMATION OF RIESZ MEANS WITH THE CRITICAL INDEX FROM H~p(Ω_n)(0
     H~p(Ω_n)(0
短句来源
     The classical probability limit theory researchs largely the weak convergence or strong approximation of partial sums of random variable sequences.
     经典的概率极限理论研究的对象主要是随机变量的部分和的弱收敛性或强收敛性,[18][36]就是这方面的经典文献。
短句来源
     The rates of strong approximation by Riesz means on compact symmetric spaces are established.
     本文在紧对称空间中给出了全测度集上Riesz平均强逼近的阶
短句来源
     The results obtained here denoted that neural networks with tunable activation functions have good property, such as more simple construction and nore strong approximation capacity, et al.
     结果表明,利用激活函数可调的神经网络具有结构简单,逼近函数能力强等特点.
短句来源
     The algorithm of system identification based on improved Elman network has quick convergent speed and strong approximation to actual object.
     文中基于改进的Elman动态网络的建模方法,收敛速度快,且模型具有很好的逼近精度;
短句来源
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  相似匹配句对
     STRONG UNIQUENESS OF NONLINEAR APPROXIMATION
     非线性逼近的强唯一性
短句来源
     STRONG UNIQUENESS OF BEST APPROXIMATION
     最佳逼近的强唯一性
短句来源
     Approximation of Aperators
     算子的逼近理论
短句来源
     THE BONE IS STRONG
     岁月流逝 骨不更年
短句来源
     On Successive Approximation
     试论逐次逼近法
短句来源
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  strong approximation
Structural properties of functions defined on a sphere are determined on the basis of the strong approximation of Fourier-Laplace series.
      
Structural properties of functions defined on a sphere on the basis of Φ-strong approximation
      
In this paper, we obtain strong approximation theorems for a single server queue withr priority classes of customers and a head-of-the-line-first discipline.
      
In this paper we inverstigate the strong approximation of a linear process with long memory to a Gaussian process.
      
Strong Approximation for Long Memory Processes with Applications
      
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In this paper, we will associated with our works to state some new advance in the theory of strong approximations. There are five parts in the paper, i. e. 1. Increments of a Wiener process. 2. Strong approximations for partial sums of IIDRV's. 3. The increments of partial sums of independent R. V. s (non-identically distri- buted). 4. Strong approximations of mixing R V. s. 5. Strong approximations for other kinds of dependent R. V.'s and functional of R. V. s.

在本文中,结合我们的工作介绍了强逼近理论的若干新进展,全文分五部分:1.Wiener过程的增量。2.独立同分布随机变量和的强逼近。3.独立不同分布随机变量和的增量。4.混合随机变量和的强逼近。5.随机变量函数及其它相依变量的强逼近。

In this paper, we get the rate of strong approximation of Random Weighting Methods on the empirical process and the quantile process, i.e. under some conditions, we have, |α_n(x)-B_n(F(x))|=O(ι(n)) a.s.P~* |α_n(x)-n~(-1/2)K(F(x), n)|=O(ι(n)) a.s.P~* |f(F~(-1)(t))Q_n~*(t)-B_n(t)|=O(ι(n)) a.s.P~* |f(F~(-1)(t))Q_n~*(t)-n~(-1/2)K(t, n)|=O(ι(n)) a.s P~* where α_n(x), Q_n~*(t), B_n(x)and n~(-1/2)K(t, n) are the empirical process, the quantile process, Brownian bridge and Kiefer process respectively.

本文研究了由随机加权法产生的经验过程及分位点过程的强逼近。

In this paper,N-union station Fork-Join queueing network is studied detailed by means of probability measure weak convergence and strong approximation in probability.We obtain weak convergence and strong approximation theorems for response time.queueing length and departure process.These theorems are useful in pracrice,and they are foundations for investigating more general Fork-Join queueing network.

本文借助于概率测度弱收敛与概率论强逼近理论,较为详细地研究了N台并联Fork-Join排队网络,得到了响应时间、队长、离去过程的弱收敛与强逼近定理。这些结果具有一定的实际意义,并为一般型Fork-Join网络的研究提供了必要的理论基础。

 
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