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  2. Blum Blum Shub - Wikipedia

    en.wikipedia.org/wiki/Blum_Blum_Shub

    Blum Blum Shub ( B.B.S.) is a pseudorandom number generator proposed in 1986 by Lenore Blum, Manuel Blum and Michael Shub [ 1] that is derived from Michael O. Rabin 's one-way function. Blum Blum Shub takes the form. where M = pq is the product of two large primes p and q. At each step of the algorithm, some output is derived from xn+1; the ...

  3. Simple random sample - Wikipedia

    en.wikipedia.org/wiki/Simple_random_sample

    Simple random sample. In statistics, a simple random sample (or SRS) is a subset of individuals (a sample) chosen from a larger set (a population) in which a subset of individuals are chosen randomly, all with the same probability. It is a process of selecting a sample in a random way. In SRS, each subset of k individuals has the same ...

  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. Hardware random number generator - Wikipedia

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

    A USB-pluggable hardware true random number generator. In computing, a hardware random number generator (HRNG), true random number generator (TRNG), non-deterministic random bit generator (NRBG), [1] or physical random number generator [2] [3] 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 ...

  6. Comparison of parser generators - Wikipedia

    en.wikipedia.org/.../Comparison_of_parser_generators

    To do so technically would require a more sophisticated grammar, like a Chomsky Type 1 grammar, also termed a context-sensitive grammar. However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity. (For example, upon encountering a variable declaration ...

  7. Randomized algorithm - Wikipedia

    en.wikipedia.org/wiki/Randomized_algorithm

    A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are ...

  8. Applications of randomness - Wikipedia

    en.wikipedia.org/wiki/Applications_of_randomness

    Randomness has many uses in science, art, statistics, cryptography, gaming, gambling, and other fields. For example, random assignment in randomized controlled trials helps scientists to test hypotheses, and random numbers or pseudorandom numbers help video games such as video poker . These uses have different levels of requirements, which ...

  9. Sampling (statistics) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(statistics)

    Sampling (statistics) In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. The subset is meant to reflect the whole population and statisticians ...