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  2. List of random number generators - Wikipedia

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

    List of random number generators. Random number generators are important in many kinds of technical applications, including physics, engineering or mathematical computer studies (e.g., Monte Carlo simulations), cryptography and gambling (on game servers ). This list includes many common types, regardless of quality or applicability to a given ...

  3. Random number generation - Wikipedia

    en.wikipedia.org/wiki/Random_number_generation

    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. This means that the particular outcome sequence will contain some patterns detectable in hindsight but impossible to foresee.

  4. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    CryptMT is a stream cipher and cryptographically secure pseudorandom number generator which uses Mersenne Twister internally. It was developed by Matsumoto and Nishimura alongside Mariko Hagita and Mutsuo Saito. It has been submitted to the eSTREAM project of the eCRYPT network.

  5. Hardware random number generator - Wikipedia

    en.wikipedia.org/wiki/Hardware_random_number...

    In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), or physical random number generator is a device that generates random numbers from a physical process capable of producing entropy (in other words, the device always has access to a physical entropy source ...

  6. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    If one has a pseudo-random number generator whose output is "sufficiently difficult" to predict, one can generate true random numbers to use as the initial value (i.e., the seed), and then use the pseudo-random number generator to produce numbers for use in cryptographic applications.

  7. Xorshift - Wikipedia

    en.wikipedia.org/wiki/Xorshift

    Xorshift random number generators, also called shift-register generators, are a class of pseudorandom number generators that were invented by George Marsaglia. They are a subset of linear-feedback shift registers (LFSRs) which allow a particularly efficient implementation in software without the excessive use of sparse polynomials . [2]

  8. Random.org - Wikipedia

    en.wikipedia.org/wiki/Random.org

    Random.org (stylized as RANDOM.ORG) is a website that produces random numbers based on atmospheric noise. In addition to generating random numbers in a specified range and subject to a specified probability distribution, which is the most commonly done activity on the site, it has free tools to simulate events such as flipping coins, shuffling cards, and rolling dice.

  9. MIXMAX generator - Wikipedia

    en.wikipedia.org/wiki/MIXMAX_generator

    The MIXMAX generator is a family of pseudorandom number generators (PRNG) and is based on Anosov C-systems (Anosov diffeomorphism) and Kolmogorov K-systems (Kolmogorov automorphism). It was introduced in a 1986 preprint by G. Savvidy and N. Ter-Arutyunyan-Savvidy and published in 1991.

  10. ACORN (random number generator) - Wikipedia

    en.wikipedia.org/.../ACORN_(random_number_generator)

    The ACORN or ″Additive Congruential Random Number″ generators are a robust family of pseudorandom number generators (PRNGs) for sequences of uniformly distributed pseudo-random numbers, introduced in 1989 and still valid in 2019, thirty years later.

  11. Category:Random number generation - Wikipedia

    en.wikipedia.org/wiki/Category:Random_number...

    M. Marsaglia's theorem. A Million Random Digits with 100,000 Normal Deviates. MIXMAX generator.