根据该理论，学习过程就是由随机信息源产生的输入信号驱动神经网络参数不断修改的过程；
The learning process of a neural network is considered the process in which neural network variables are changed with a time series of input signals generated from a stochastic information source.
虚拟化可能在利用这样的信息源上存在缺陷，或者说在同一台主机上容纳多个虚拟机运行环境可能会穷尽可用的信息源，导致薄弱的随机数生成机制。
Virtualization might have flawed mechanisms for tapping that entropy source, or hav-ing several VMEs on the same host might exhaust the available entropy, leading to weak random number generation.
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