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  2. Blum Blum Shub - Wikipedia

    en.wikipedia.org/wiki/Blum_Blum_Shub

    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 x n+1; the output is commonly either the bit parity of x n+1 or one or more of the least significant bits of x n+1.

  3. ACORN (random number generator) - Wikipedia

    en.wikipedia.org/.../ACORN_(random_number_generator)

    The main advantages of ACORN are simplicity of concept and coding, speed of execution, long period length, and mathematically proven convergence. [3] The algorithm can be extended, if future applications require “better quality” pseudo random numbers and longer period, by increasing the order and the modulus as required.

  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. Linear congruential generator - Wikipedia

    en.wikipedia.org/wiki/Linear_congruential_generator

    The second row is the same generator with a seed of 3, which produces a cycle of length 2. Using a = 4 and c = 1 (bottom row) gives a cycle length of 9 with any seed in [0, 8]. A linear congruential generator (LCG) is an algorithm that yields a sequence of pseudo-randomized numbers calculated with a discontinuous piecewise linear equation.

  6. Lagged Fibonacci generator - Wikipedia

    en.wikipedia.org/wiki/Lagged_Fibonacci_generator

    The maximum period of lagged Fibonacci generators depends on the binary operation .If addition or subtraction is used, the maximum period is (2 k − 1) × 2 M−1.If multiplication is used, the maximum period is (2 k − 1) × 2 M−3, or 1/4 of period of the additive case.

  7. Josephus problem - Wikipedia

    en.wikipedia.org/wiki/Josephus_problem

    The most elegant form of the answer involves the binary representation of size n: () can be obtained by a one-bit left cyclic shift of n itself. If n is represented in binary as n = 1 b 1 b 2 b 3 … b m {\displaystyle n=1b_{1}b_{2}b_{3}\dots b_{m}} , then the solution is given by f ( n ) = b 1 b 2 b 3 … b m 1 {\displaystyle f(n)=b_{1}b_{2}b ...

  8. Lehmer random number generator - Wikipedia

    en.wikipedia.org/wiki/Lehmer_random_number_generator

    The generator computes an odd 128-bit value and returns its upper 64 bits. This generator passes BigCrush from TestU01, but fails the TMFn test from PractRand. That test has been designed to catch exactly the defect of this type of generator: since the modulus is a power of 2, the period of the lowest bit in the output is only 2 62, rather than ...

  9. Permuted congruential generator - Wikipedia

    en.wikipedia.org/.../Permuted_Congruential_Generator

    Finally, if a cycle length longer than 2 128 is required, the generator can be extended with an array of sub-generators. One is chosen (in rotation) to be added to the main generator's output, and every time the main generator's state reaches zero, the sub-generators are cycled in a pattern which provides a period exponential in the total state ...

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