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  2. Category:Pseudorandom number generators - Wikipedia

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

    What links here; Related changes; Upload file; ... Get shortened URL; Download QR code; ... R. Random number generator attack; Random seed;

  3. /dev/random - Wikipedia

    en.wikipedia.org/wiki/Dev/random

    The /dev/urandom device typically was never a blocking device, even if the pseudorandom number generator seed was not fully initialized with entropy since boot. Not all operating systems implement the same methods for /dev/random and /dev/urandom. This special file originated in Linux in 1994. It was quickly adopted by other Unix-like operating ...

  4. List of random number generators - Wikipedia

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

    Default generator in R and the Python language starting from version 2.3. Xorshift: 2003 G. Marsaglia [26] It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence.

  5. Random seed - Wikipedia

    en.wikipedia.org/wiki/Random_seed

    A random seed (or seed state, or just seed) is a number (or vector) used to initialize a pseudorandom number generator. A pseudorandom number generator's number sequence is completely determined by the seed: thus, if a pseudorandom number generator is later reinitialized with the same seed, it will produce the same sequence of numbers.

  6. 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 ...

  7. Multiply-with-carry pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Multiply-with-carry...

    This makes p − 1 = ab r easy to factor, making it practical to establish the period of very large generators. The modified procedure is called complementary-multiply-with-carry (CMWC), and the setup is the same as that for lag-r MWC: multiplier a, base b, and r + 1 seeds, x 0, x 1, x 2, ..., x r−1, and c r−1.

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  9. Pseudorandom generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_generator

    Noam Nisan (1992) showed that this derandomization can actually be achieved with a pseudorandom generator of seed length (⁡) that fools all (⁡)-space machines. Nisan's generator has been used by Saks and Zhou (1999) to show that probabilistic log-space computation can be simulated deterministically in space O ( log 1.5 ⁡ n ...