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  2. List of random number generators - Wikipedia

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

    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 use case.

  3. 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.

  4. Permuted congruential generator - Wikipedia

    en.wikipedia.org/.../Permuted_Congruential_Generator

    A permuted congruential generator (PCG) is a pseudorandom number generation algorithm developed in 2014 by Dr. M.E. O'Neill which applies an output permutation function to improve the statistical properties of a modulo-2 n linear congruential generator.

  5. Mersenne Twister - Wikipedia

    en.wikipedia.org/wiki/Mersenne_Twister

    Mersenne Twister. The Mersenne Twister is a general-purpose pseudorandom number generator (PRNG) developed in 1997 by Makoto Matsumoto [ ja] (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.

  6. 6 - Wikipedia

    en.wikipedia.org/wiki/6

    6 is a pronic number and the only semiprime to be. It is the first discrete biprime (2 × 3) which makes it the first member of the (2 × q) discrete biprime family, where q is a higher prime. All primes above 3 are of the form 6n ± 1 for n ≥ 1. As a perfect number: 6 is related to the Mersenne prime 3, since 2 1 (2 2 – 1) = 6.

  7. 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), is an algorithm for generating a sequence of numbers whose properties approximate the properties of sequences of random numbers.

  8. Hamming code - Wikipedia

    en.wikipedia.org/wiki/Hamming_code

    In mathematical terms, Hamming codes are a class of binary linear code. For each integer r ≥ 2 there is a code-word with block length n = 2r − 1 and message length k = 2r − r − 1. Hence the rate of Hamming codes is R = k / n = 1 − r / (2r − 1), which is the highest possible for codes with minimum distance of three (i.e., the minimal ...

  9. Linear code - Wikipedia

    en.wikipedia.org/wiki/Linear_code

    A linear code of length n and dimension k is a linear subspace C with dimension k of the vector space where is the finite field with q elements. Such a code is called a q -ary code. If q = 2 or q = 3, the code is described as a binary code, or a ternary code respectively. The vectors in C are called codewords.

  10. Pseudorandom generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_generator

    Pseudorandom generator. In theoretical computer science and cryptography, a pseudorandom generator (PRG) for a class of statistical tests is a deterministic procedure that maps a random seed to a longer pseudorandom string such that no statistical test in the class can distinguish between the output of the generator and the uniform distribution.

  11. Combined linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Combined_Linear_Congruenti...

    A combined linear congruential generator (CLCG) is a pseudo-random number generator algorithm based on combining two or more linear congruential generators (LCG). A traditional LCG has a period which is inadequate for complex system simulation.