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  2. List of random number generators - Wikipedia

    en.wikipedia.org/wiki/List_of_random_number...

    These approaches combine a pseudo-random number generator (often in the form of a block or stream cipher) with an external source of randomness (e.g., mouse movements, delay between keyboard presses etc.). /dev/random – Unix-like systems; CryptGenRandom – Microsoft Windows; Fortuna

  3. Wichmann–Hill - Wikipedia

    en.wikipedia.org/wiki/Wichmann–Hill

    Wichmann–Hill is a pseudorandom number generator proposed in 1982 by Brian Wichmann and David Hill. [1] It consists of three linear congruential generators with different prime moduli, each of which is used to produce a uniformly distributed number between 0 and 1. These are summed, modulo 1, to produce the result. [2]

  4. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士). [ 1][ 2] Its name derives from the choice of a Mersenne prime as its period length. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.

  5. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    Dice are an example of a mechanical hardware random number generator. When a cubical die is rolled, a random number from 1 to 6 is obtained. Random number generation is a process by which, often by means of a random number generator (RNG), a sequence of numbers or symbols that cannot be reasonably predicted better than by random chance is generated.

  6. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    A pseudorandom number generator ( PRNG ), also known as a deterministic random bit generator ( DRBG ), [ 1] is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers. The PRNG-generated sequence is not truly random, because it is completely determined by an initial value ...

  7. Lehmer random number generator - Wikipedia

    en.wikipedia.org/wiki/Lehmer_random_number_generator

    The Lehmer random number generator[ 1 ] (named after D. H. Lehmer ), sometimes also referred to as the Park–Miller random number generator (after Stephen K. Park and Keith W. Miller), is a type of linear congruential generator (LCG) that operates in multiplicative group of integers modulo n. The general formula is.

  8. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    the (pseudo-random) number generator has certain characteristics (e.g. a long "period" before the sequence repeats) the (pseudo-random) number generator produces values that pass tests for randomness; there are enough samples to ensure accurate results; the proper sampling technique is used; the algorithm used is valid for what is being modeled

  9. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator ( LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation. The method represents one of the oldest and best-known pseudorandom number generator algorithms.