依概率收敛

依概率收敛与依分布收敛的关系

Relation between Convergence in Probability and Convergence in Distribution

在此基础上，证明了二叉树结构编码的遗传算法在对选择算子进行改进后依概率收敛到最优解。

On the basis of these studies , improved genetic algorithm convergence in probability is proven .

本文利用大偏差理论研究了Annealing算法的依概率收敛速度。

Using large deviation theory the rate of convergence for Annealing algorithm was estimated .

首先得出马尔可夫链大偏差Ⅰ函数的下界，并利用它得出Annealing算法依概率收敛速度具有状态总数的分数幂阶。

A lower bound of I function of large deviation for Markov chains was presented and applied to obtain the conclusion that the rate of convergence in propability for Annealing algorithm has a order of fractional power of number of states .

提出均值变点的Subsampling检验，证明了Subsampling的经验分布是依概率收敛于累积和检验统计量在原假设下的极限分布，而且这种收敛性质在数据存在变点时也是成立的。

We propose the Subsampling method to detect changes and show that the empirical distribution of subsampling test converges in probability to that of CUSUM test under null hypothesis .

散布阵及主成分的投影寻踪估计依概率收敛的速度

Convergence rate of projection pursuit estimators for dispersion matrices

分析结果表明人口迁移算法依概率收敛到全局最优解。

It is proved that the algorithm converges to the global optimum in probability .

运用概率论的有关理论证明了该算法依概率收敛到全局最优解。

It is proved by means of probability that the algorithm converges to the global optimum in probability .

在超临界情形下，是依概率收敛到0的；

Whereas in the supercritical case , it converges to 0 . In the critical case , if k / (?)

此外还得到了一般随机变量阵列的完全收敛性与依概率收敛性。

In the other direction , the complete convergence and the convergence in probability for arbitrary random variable arrays are obtained .

由依概率收敛推出γ阶收敛的条件建立数学模型确定三率指标经济合理地开采利用黄金矿产资源

To establish mathematic model and determine the three rate indices in order to economically and reasonably exploit the gold mineral resourses

主要把数列收敛的一些性质引进到随机变量依概率收敛中来，并加以证明。

The property in convergence of sequence of number was imported to convergence in probability and proved it in this paper .

由随机变量序列几乎处处收敛可推出其依概率收敛，进而可推出其依分布收敛，可见判别几乎处处收敛的重要性。

Through almost sure convergence of random variables , the probability convergence can be derived ; and further the weak convergence can be derived .

在相邻采样点的相关性不趋于零的情形下，我们证明了该估计量的依概率收敛性。

We proved a preliminary result that it can converge to the change-point with probability when the correlation between adjacent samples does not tend to zero .

主要讨论了几乎处处收敛与依概率收敛，完全收敛与几乎处处收敛的关系。

In this paper we discuss the relation between almost sure convergence and convergence in probability , and the relation between complete convergence and almost sure convergence .

另一方面，本文将随机个体之间的差异信息引入差分进化算法中，设计了一个新的二进制进化算法来求解离散优化问题，并证明了该算法的依概率收敛性。

To solve discrete optimization problems , on the other aspect , the difference information between stochastic individuals are embedded into the DE algorithm and a new binary evolution-ary algorithm is obtained .

讨论并建立了概率意义下取全局最小值的一个充分必要条件，证明了算法LDM是依概率测度收敛的。

Discuss and establish a sufficient and necessary condition for the global optimum in probability measure , and prove that the LDM algorithm is convergence in probability .

本文还证明了该混合优化方法依概率1收敛于全局最优解。

This paper also proves that this new algorithm is a global optimization algorithm .

关于算法分析的定理证明了这种混合算法对于紧致集内的权向量构成的任意连续函数能依概率1收敛于全局极小值。

It is shown that this algorithm ensures convergence to a global minimum with probability1in a compact region of a weight vector space .

本文采用离散线性系统理论对拟态物理学优化算法的收敛性进行分析，得出算法收敛的充分必要条件，证明了该算法是依概率1收敛的。

The necessary and sufficient conditions for APO convergence are deduced through analyzing APO algorithm based on discrete-time linear system theory . And APO algorithm converge to the vicinity of global optimum with probability one is proved .

讨论了具有一般约束的全局优化问题，给出该问题的一个随机搜索算法，证明了该算法依概率1收敛到问题的全局最优解。

In this paper , the global optimization problems with general constraints are considered . A stochastic search algorithm to solve these problems is proposed . It is shown that the algorithm converges to a global optimal solution with probability one .