1) in probability
依概率
1.
For the problem that the effectivenes of Genetic Algorithm is shown generally by numerical experiments,the convergence in probability of a class of hybrid genetic Algorithm based on the condition of three hypothesizes is proved in the paper and the conclusion is drawn that the convergence in probability is not unchanged if mutation operator of sub-population Ⅱ is changed under the algorithm frame.
针对遗传算法的有效性一般是通过数值实验来说明这一问题,本文在三个假设的条件下给出了一类混合遗传算法依概率收敛的证明,而且得到了在此算法的框架下通过改变子种群Ⅱ的变异算子而不改变依概率收敛特性的结论。
3) probability convergence
依概率收敛
1.
Through almost sure convergence of random variables, the probability convergence can be derived; and further the weak convergence can be derived.
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。
2.
In this paper,we study the mutual relations of complete convergence,almost everywhere converge,convergence in the mean of order r and the probability convergence.
研究了复值随机变量序列的完全收敛,几乎处处收敛,r阶平均收敛,依概率收敛之间的相互关系,得到了几个有意义的结论。
3.
In this paper,we discuss the mutual relation of complete convergence,almost everywhere converge,convergence in the mean of order r,probability convergence and convergence in distribution for real valued random variable sequence{ξ n},under the complete probability space.
在完备的概率空间 (Ω，， P)下，讨论了实值随机变量序列 {ξ n}的完全收敛、几乎处处收敛、 r次平均收敛、依概率收敛、依分布收敛之间的相互关系，得到若干有意义的常用结论。
4) convergence in probability
依概率收敛
1.
This paper applying probability knowledge,such as convergence in probability and control convergence theorem,generalizes the theorem in paper [2],obtains the general theorem of solving the limit of a class of multi-integral,and states the priority of using the theorem through the concrete example.
文献[1]和文献[2]举例说明了运用概率思想求多重积分极限方面的应用,本文综合应用依概率收敛和控制收敛定理等概率知识,推广文献[2]的定理,给出求解一类多重积分极限的一般性定理。
2.
Definitions of convergence in probability,convergence in distribution and almost sure convergence of sequences of random variables are given.
给出了随机变量列的依概率收敛、依分布收敛、几乎必然收敛的定义,举例说明了其应用,并研究了三种收敛性之间的相互关系。
3.
The property in convergence of sequence of number was imported to convergence in probability and proved it in this paper.
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。
5) stabilization in probability
依概率稳定
1.
By using It s differentiation rule, nonlinear damping and adaptive Backstepping procedure, the input-to-state stable controller of global stabilization in probability is developed.
基于It 微分规则、非线性阻尼和Backstepping算法 ,设计了全局依概率稳定的输入状态稳定控制器 ,具有很强的参数鲁棒稳定特性 ;根据Swapping技术 ,设计了两个滤波器 ,把一个动态参数模型转化为一个静态模型 ,基于梯度算法 ,设计了参数自适应律 ,确保扰动有界 ,最后 ,给出了系统的性能估计 ,仿真结果表明该控制算法的有效性 。
6) generation in probability
依概率生成
补充资料：依概率收敛
依概率收敛
convergence in probability
依概率收敛【以.ve咭e岭iop州肠bili勺;仁.却口MocTI..班侧祖1，.洲，.] 定义在某个概率空间(Q，了，P)上的随机变量序列X:，戈，…向一个随机变量X的依下述方式定义的收敛:戈几X，如果对任何。>o， 尸{}弋一引>目*0当””0O时在数学分析中，这种收敛形式称为依测度收敛(conver-罗nce in measure).从依概率收敛可推出依分布收徽(conve卿no in distribution).B.H.E片rK习班o:撰【补注】亦见概率测度的弱收敛(weak convergen沈ofprobability meas、、res):收徽的类型(conver罗n件，types()f);分布收敛(dlstributions.~er罗n优of).
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