- 更多网络例句与几乎必然收敛相关的网络例句 [注：此内容来源于网络，仅供参考]
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First, we present various new convergence concepts for sequence of fuzzy random variables, including convergence sure, convergence almost sure, uniform convergence, uniform convergence almost sure, almost uniform convergence, convergence in chance measure, and their corresponding weak convergence. Second, the relations among some types of convergence are studied. Finally, we design some algorithms about fuzzy random simulations to compute the mean chance of fuzzy random event, find the optimistic value of a return function, and evaluate the expected value of a fuzzy random variable.
首先，提出了几类模糊随机变量序列的收敛性概念，包括：必然收敛、几乎必然收敛、一致收敛、几乎必然一致收敛、近一致收敛、依机会测度收敛以及与以上概念相对应的弱收敛；其次，讨论了收敛性之间的关系；最后我们设计了模糊随机模拟算法，用于计算模糊随机事件的平均机会，寻找收益函数的乐观值，以及估计模糊随机变量的期望值。
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First, we present various new convergence concepts for sequence of fuzzy random variables, including convergence sure, convergence almost sure, uniform convergence, uniform convergence almost sure, almost uniform convergence, convergence in chance measure, and their corresponding weak convergence.
首先，提出了几类模糊随机变量序列的收敛性概念，包括：必然收敛、几乎必然收敛、一致收敛、几乎必然一致收敛、近一致收敛、依机会测度收敛以及与以上概念相对应的弱收敛；其次，讨论了收敛性之间的关系；最后我们设计了模糊随机模拟算法，用于计算模糊随机事件的平均机会，寻找收益函数的乐观值，以及估计模糊随机变量的期望值。
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Classical limit theory includes the central limit theory, the law of large numbers, and the law of iterated logarithm etc.
经典的极限理论包括中心极限定理，大数律，重对数律等等，相对于收敛性来讲，就是依分布收敛，依概率收敛，和几乎必然收敛等等。
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In Chapter 3 Firstly, the exponential stability in mean square and almost sure exponential stability for neutral stochstic neural networks with time-varying delay can be discussed by using the linear matrix inequality and the semimartingale convergence theorem; And our sufficient conditions are less conserative; Secondly, by utilizing the fixed point theorem, some sufficient and necessary conditions ensuring the asymp- totic stability in mean square for neutral stochastic neural networks with time-varying delays can be given.
第三章首先，利用线性矩阵不等式方法和半鞅收敛定理，考虑了一类具变时滞中立型随机神经网络的二阶矩指数稳定性和几乎必然指数稳定性，所得到的条件保守性要好；其次，采用不动点方法，给出了具变时滞中立型随机神经网络的二阶矩渐近稳定性的充要条件。
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This article gives some almost sure convergence properties for the partial sums of random variable sequence by using the strong law of large numbers, which were obtained by Hu.
本文利用胡舒合等获得的强大数定律，给出了随机变量序列部分和的一些几乎必然收敛性，并给出了结果在PA、NA和两两NQD序列场合下的应用。
- 更多网络解释与几乎必然收敛相关的网络解释 [注：此内容来源于网络，仅供参考]
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almost admissible decision function：几乎可容决策函数
几乎可容决策函数 almost admissible decision function | 几乎到处收敛 almost certain convergence | 几乎必然地 almost certainly
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almost bounded function：殆有界函数
almost all 几乎处处 | almost bounded function 殆有界函数 | almost certain convergence 几乎必然收敛
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almost certain convergence：几乎必然收敛
almost bounded function 殆有界函数 | almost certain convergence 几乎必然收敛 | almost complex manifold 殆复廖
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almost certain convergence：几乎到处收敛
几乎可容决策函数 almost admissible decision function | 几乎到处收敛 almost certain convergence | 几乎必然地 almost certainly
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almost complex manifold：殆复廖
almost certain convergence 几乎必然收敛 | almost complex manifold 殆复廖 | almost convergent sequence 殆收敛序列
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almost everywhere, a.e：几乎处处
几乎必然收敛|almost sure convergence | 几乎处处|almost everywhere, a.e | 几乎处处收敛|convergence almost everywhere
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almost surely：殆必;几乎必然
准环 almost ring | 殆必;几乎必然 almost surely | 殆必收敛 almost surely convergent
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almost surely：几乎必然地
几乎到处收敛 almost sure convergence | 几乎必然地 almost surely | 欧特(Alter)周期图 Alter periodiagram