UDRs, like random number generators and current date/time functions, are variant and therefore cannot be used.
和随机数生成程序、当前日期/时间函数一样，UDR通常是变化的，因此不能用于函数索引。
And then, methods of the parallel implementing, relative merits and test methods in parallel random number generators are described.
重点介绍了并行随机数生成器的实现方式、优缺点和检测方法。
NOTE: when I said "random" in this post, I naturally mean the pseudorandom number generators computers use, which isn't really random, but was more than close enough for our project.
注意：本文中的“随机”是指计算机使用的伪随机数，而非真随机，但从项目中来看已经不错了。
In this paper, it firstly gives out some common random number generators and their defects; and then presents a new random number generator and its algorithm, and gives some statistical tests.
首先介绍一些常见的随机数发生器及其优缺点，然后给出了一种新的随机数发生器及其算法，并对它产生的随机数序列进行了统计检验。
Use the Boost random-number generators.
使用Boost随机数生成器。
It typically USES random number 5 generators to generate multiple scenarios of a model by repeatedly sampling values from the probability distributions for the uncertain variables.
它使用随机数5生成器通过重复地根据不确定变量的概率分布采样来生成模型的多重情境。
To design a gaussian random number generator used for channel simulation and coder performance test, high-speed universal random number and correlated stochastic series generators are studied.
为设计一个用于信道仿真和编码器性能测试的高速高斯随机数发生器，研究了适于硬件实现的高速通用的连续随机变量和随机序列产生法。
To design a gaussian random number generator used for channel simulation and coder performance test, high-speed universal random number and correlated stochastic series generators are studied.
为设计一个用于信道仿真和编码器性能测试的高速高斯随机数发生器，研究了适于硬件实现的高速通用的连续随机变量和随机序列产生法。
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