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PRBS generators are used in telecommunication, such as in analog-to-information conversion, [2] but also in encryption, simulation, correlation technique and time-of-flight spectroscopy. The most common example is the maximum length sequence generated by a (maximal) linear feedback shift register (LFSR).
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 ...
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. The xorwow generator is the default generator in the CURAND library of the nVidia CUDA application programming interface for graphics processing units.
For example, if the taps are at the 16th, 14th, 13th and 11th bits (as shown), the feedback polynomial is + + + + The "one" in the polynomial does not correspond to a tap – it corresponds to the input to the first bit (i.e. x 0, which is equivalent to 1). The powers of the terms represent the tapped bits, counting from the left.
To perform such a simulation, it is sufficient to construct pseudorandom generators against the family F of all circuits of size s(n) whose inputs have length n and output a single bit, where s(n) is an arbitrary polynomial, the seed length of the pseudorandom generator is O(log n) and its bias is ⅓.
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.
In theoretical computer science, a pseudorandom generator for low-degree polynomials is an efficient procedure that maps a short truly random seed to a longer pseudorandom string in such a way that low-degree polynomials cannot distinguish the output distribution of the generator from the truly random distribution. That is, evaluating any low ...
An xorshift* generator applies an invertible multiplication (modulo the word size) as a non-linear transformation to the output of an xorshift generator, as suggested by Marsaglia. [1] All xorshift* generators emit a sequence of values that is equidistributed in the maximum possible dimension (except that they will never output zero for 16 ...