设为随机变量序列，文章在较弱的混合速度且非同分布的条件下证明了其完全收敛性的一个结果。
Let be a -mixing random variable sequence, and it is proved to be a theorem of complete convergence under the condition of slow mixing speed and non-identity distribution.
本文提出了类条件概率密度随机变量（特征）空间离散化及类条件概率分布估计方法。
A discrete method for stochastic variable (features) space of class-conditional-probability density and estimation method for class-conditional -probability distribution is proposed.
相依随机变量部分和过程的滞后增量有多大？本文回答了这个问题。在适当的混合条件下，有。
How big are the lag increments of partial sums of dependent random variables? In this paper, the question will be answered: in suitable mixing conditions, we have.
相依随机变量部分和过程的滞后增量有多大？本文回答了这个问题。在适当的混合条件下，有。
How big are the lag increments of partial sums of dependent random variables? In this paper, the question will be answered: in suitable mixing conditions, we have.
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