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We describe von Neumann’s elegant idea for sampling from the exponential distribution, Forsythe’s generalization for sampling from a probability distribution whose density has the form exp(-G(x)), where G(x) is easy to compute (e.g. a polynomial), and my refinement of these ideas to give an efficient algorithm for generating pseudo-random numbers with a normal distribution. Later developments are also mentioned.

生成讲解博客的中文版本

生成AI智能校验的中文版本