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  2. 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.

  3. List of random number generators - Wikipedia

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

    However, generally they are considerably slower (typically by a factor 2–10) than fast, non-cryptographic random number generators. These include: Stream ciphers. Popular choices are Salsa20 or ChaCha (often with the number of rounds reduced to 8 for speed), ISAAC, HC-128 and RC4. Block ciphers in counter mode.

  4. Random number - Wikipedia

    en.wikipedia.org/wiki/Random_number

    Random number. 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. A random number is generated by a random ( stochastic) process such as throwing Dice. Individual numbers can't be predicted, but the likely result of generating a large quantity of numbers ...

  5. 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.

  6. Random number table - Wikipedia

    en.wikipedia.org/wiki/Random_number_table

    Random number tables have been used in statistics for tasks such as selected random samples. This was much more effective than manually selecting the random samples (with dice, cards, etc.). Nowadays, tables of random numbers have been replaced by computational random number generators . If carefully prepared, the filtering and testing ...

  7. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    To illustrate, imagine if a simple 32 bit linear congruential pseudo-random number generator of the type supplied with most programming languages (e.g., as the 'rand' or 'rnd' function) is used as a source of keys. There will only be some four billion possible values produced before the generator repeats itself.

  8. 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 ...

  9. 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.