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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; RDRAND instructions (called Intel Secure Key by Intel ...

  3. Module:Random - Wikipedia

    en.wikipedia.org/wiki/Module:Random

    Called from other Lua modules.-----function p. main (funcName, args, listType)-- Sets the seed for the random number generator and passes control over to the other functions. local same = yesno (args. same) if not same then-- Generates a different number every time the module is called, even from the same page.

  4. 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 is generated that cannot be reasonably predicted better than by random chance.

  5. 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.

  6. Random number - Wikipedia

    en.wikipedia.org/wiki/Random_number

    [2] [3] It has been described as "several oscillators combine their outputs and that odd waveform is sampled asynchronously." [ 4 ] These numbers, however, were only 32 bit, at a time when export controls were on 56 bits and higher, so they were not state of the art.

  7. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

  8. Generator (computer programming) - Wikipedia

    en.wikipedia.org/wiki/Generator_(computer...

    In Python, a generator can be thought of as an iterator that contains a frozen stack frame. Whenever next() is called on the iterator, Python resumes the frozen frame, which executes normally until the next yield statement is reached. The generator's frame is then frozen again, and the yielded value is returned to the caller.

  9. Middle-square method - Wikipedia

    en.wikipedia.org/wiki/Middle-square_method

    Consider the following: If a 3-digit number is squared, it can yield a 6-digit number (e.g. 540 2 = 291600). If there were to be middle 3 digits, that would leave 6 − 3 = 3 digits to be distributed to the left and right of the middle. It is impossible to evenly distribute these digits equally on both sides of the middle number, and therefore ...