Other considerations Random numbers uniformly distributed between 0 and 1 can be used to generate random numbers of any desired distribution by passing them through the inverse (CDF) of the desired distribution (see ). Li and Wang proposed a method of testing random numbers based on laser chaotic entropy sources using Brownian motion properties. Wang and Nicol proposed a distance-based statistical testing technique that is used to identify the weaknesses of several random generators. Good Algorithms for Random Number Generation' (PDF. Random number generation is the generation. 2011), Automatic Nonuniform Random Variate Generation. It is generally hard to use statistical tests to validate the generated random numbers. Some methods of random number generation are better than others. An example would be the TRNG9803 hardware random number generator, which uses an entropy measurement as a hardware test, and then post-processes the random sequence with a shift register stream cipher. ![]() ![]() Generated random numbers are sometimes subjected to statistical tests before use to ensure that the underlying source is still working, and then post-processed to improve their statistical properties. And a software bug in a pseudo-random number routine, or a hardware bug in the hardware it runs on, may be similarly difficult to detect.
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