Search results
Results From The WOW.Com Content Network
Widely used in many programs, e.g. it is used in Excel 2003 and later versions for the Excel function RAND [8] and it was the default generator in the language Python up to version 2.2. [9] Rule 30: 1983 S. Wolfram [10] Based on cellular automata. Inversive congruential generator (ICG) 1986 J. Eichenauer and J. Lehn [11] Blum Blum Shub: 1986
The MIXMAX generator is a family of pseudorandom number generators (PRNG) and is based on Anosov C-systems (Anosov diffeomorphism) and Kolmogorov K-systems (Kolmogorov automorphism). It was introduced in a 1986 preprint by G. Savvidy and N. Ter-Arutyunyan-Savvidy and published in 1991.
The following is an implementation of the CMWC algorithm in the C programming language. Also, included in the program is a sample initialization function. In this implementation the base is 2 32 −1 and lag r=4096. The period of the resulting generator is about .
An xorshift+ generator can achieve an order of magnitude fewer failures than Mersenne Twister or WELL. A native C implementation of an xorshift+ generator that passes all tests from the BigCrush suite can typically generate a random number in fewer than 10 clock cycles on x86, thanks to instruction pipelining. [12]
Fortuna is a cryptographically secure pseudorandom number generator (CS-PRNG) devised by Bruce Schneier and Niels Ferguson and published in 2003. It is named after Fortuna, the Roman goddess of chance. FreeBSD uses Fortuna for /dev/random and /dev/urandom is symbolically linked to it since FreeBSD 11. [1] Apple OSes have switched to Fortuna ...
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 ...
An astrophysical Monte Carlo simulator examined the time to generate 10 7 64-bit random numbers using RDRAND on a quad-core Intel i7-3740 QM processor. They found that a C implementation of RDRAND ran about 2× slower than the default random number generator in C, and about 20× slower than the Mersenne Twister.
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 ...