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We get the two edge blocking convergencetheorem of sequence of fuzzy numbers and the almost everywhere cut-convergence theorem ofmonotone bounded sequence of fuzzy numbers, and point out that monotone bounded sequenceof fuzzy numbers may not cut-converges and converges.

讨论了模糊数列的收敛、截收敛、几乎处处截收敛性,得到了模糊数列收敛的夹逼定理及单调序有界模糊数列必几乎处处截收敛定理,并指出了单调序有界模糊数列未必截收敛、收敛。

In 1947,Hus and Robbin defined the complete convergence,which is stronger than almost everywhere convergence.

Hus和Robbin于1947年提出了完全收敛性的概念,完全收敛比几乎处处收敛更强。

In 1947, Hus and Robbin defined the complete convergence, which is stronger than almost everywhere convergence.

Hus和Robbin于1947年提出了完全收敛性的概念,完全收敛比几乎处处收敛条件更严格。

Stochastic theory and other correlative theories are used to analyze IGA, and the immune extend population sequence formed by IGA is proved to be an aperiodic irreducible ergodic Markov chain.

同时在纯数学意义上拓展讨论,就IGA的一般收敛理论进行分析,证明了概率弱收敛、几乎处处弱收敛、渐进收敛等性质。

Convergence supper martingal and analytical method, a strong limit theorem for Laplace distribution is obtained.

利用似然比构造几乎处处收敛的上鞅,结合分析方法,给出了 Laplace分布的一个强极限定理。

With four continuity of non-additive set function and the relation of four convergences of the measurable function sequence,four forms Lebesgue theorem about measurable closed-valued functions on monotone measure space are discussed,respectively.

在经典测度论中,Lebesgue定理刻画了实值可测函数序列几乎处处收敛和依测度收敛之间的关系。1984~1986年,王震源[9]先后提出了较弱的"自连续"、"零可加"、"伪自连续"、"伪零可加"等重要概念,讨论了模糊测度空间上单值可测函数序列各种收敛之间的关系,推广了经典测度论中著名的Lebesgue定理以及其他定理。

Finally,the inequality of maximal operators of tree martingale transformsis applied for obtaining the UMD space valued Vilenkin system and the sum ofVilenkin-Fourier series of UMD space valued Vilenkin system is convergent a.e.or convergent in LP-norm.

最后,应用UMD空间值树鞅鞅变换的极大算子不等式,我们获得了UMD空间值Vilenkin系统以范数收敛和几乎处处收敛定理,即Carleson定理的扩展。

The almost sure convergence properties of general Jamison weighted sums of submartingale difference random sequence sis was discussed.

通过讨论下鞅差序列的广义 Jamison型加权和的几乎处处收敛性,获得了比独立情形还强的 Jamison定理和 Marcinkiewicz强大数律,推广和改进了这两个定

This paper discussed almost everywhere upper semiconvergence of optimal solution set of empirical approximations for stochastic programs.

本文对随机规划经验逼近最优解集的几乎处处上半收敛性进行了研究。

Firstly, an empirical approximation model of stochastic programming is obtained by replacing the probability measure of original program with empirical probability measure. Sequentially, the constrained stochastic programming is transformed into an equivalent unconstrained stochastic programming. Finally, using the epi-convergence theory, the almost everywhere upper semiconvergence of optimal solution set of empirical approximations for stochastic programming is obtained.

首先通过经验概率测度替代初始规划的概率测度得到随机规划的经验逼近模型,然后将带有约束的随机规划问题转化成与其等价的无约束的随机规划问题,最后利用上图收敛性理论,给出了随机规划经验逼近最优解集的几乎处处上半收敛性。

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