A close encounter with Random Numbers

Subrata Das, P. Dasgupta, A. Pandey, Pabitra Roy
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引用次数: 1

Abstract

Performance profiling or empirical testing, and statistical testing of algorithms for NP-complete problems is typically based on random sample testing. Random values constitute a good source of data for testing the effectiveness of a computer algorithm. Random number generation is an absolute proposition. As such, generally the concentration is on realistic pseudorandom number generation. There are numerous pseudorandom number generation algorithms. We propose here another drop in the sea which is at least as efficient as the existing algorithms and simpler in certain respects.
与随机数的近距离接触
np完全问题算法的性能分析或经验测试和统计测试通常基于随机样本测试。随机值是测试计算机算法有效性的一个很好的数据来源。随机数生成是一个绝对命题。因此,通常关注的是真实的伪随机数生成。有许多伪随机数生成算法。我们在这里提出的另一种算法是沧海一粟,它至少和现有的算法一样有效,而且在某些方面更简单。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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