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is exactly the Lehmer random number generator output sequence y n = ay n − 1 mod (ab − 1), reduced modulo b. Choosing a different initial value y 0 merely rotates the cycle of x' s. Complementary-multiply-with-carry generators
SP800-90 series on Random Number Generation, NIST; Random Number Generation in the GNU Scientific Library Reference Manual; Random Number Generation Routines in the NAG Numerical Library; Chris Lomont's overview of PRNGs, including a good implementation of the WELL512 algorithm; Source code to read data from a TrueRNG V2 hardware TRNG
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.
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.
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.
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. The Mersenne Twister was designed specifically to rectify most of the flaws found in older PRNGs.
KISS (Keep it Simple Stupid) is a family of pseudorandom number generators introduced by George Marsaglia. [1] [2] [3] Starting from 1998 Marsaglia posted on various newsgroups including sci.math, comp.lang.c, comp.lang.fortran and sci.stat.math several versions of the generators.
In 1992, further results were published, [11] implementing the ACORN Pseudo-Random Number Generator in exact integer arithmetic which ensures reproducibility across different platforms and languages, and stating that for arbitrary real-precision arithmetic it is possible to prove convergence of the ACORN sequence to k-distributed as the ...