Improving the Quality of Random Number Generators by Applying a Simple Ratio Transformation

12/21/2016
by   Michael Kolonko, et al.
0

It is well-known that the quality of random number generators can often be improved by combining several generators, e.g. by summing or subtracting their results. In this paper we investigate the ratio of two random number generators as an alternative approach: the smaller of two input random numbers is divided by the larger, resulting in a rational number from [0,1]. We investigate theoretical properties of this approach and show that it yields a good approximation to the ideal uniform distribution. To evaluate the empirical properties we use the well-known test suite TestU01. We apply the ratio transformation to moderately bad generators, i.e. those that failed up to 40% of the tests from the test battery Crush of TestU01. We show that more than half of them turn into very good generators that pass all tests of Crush and BigCrush from TestU01 when the ratio transformation is applied. In particular, generators based on linear operations seem to benefit from the ratio, as this breaks up some of the unwanted regularities in the input sequences. Thus the additional effort to produce a second random number and to calculate the ratio allows to increase the quality of available random number generators.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/03/2018

A Search for Good Pseudo-random Number Generators : Survey and Empirical Studies

In today's world, several applications demand numbers which appear rando...
research
01/15/2020

Computationally easy, spectrally good multipliers for congruential pseudorandom number generators

Congruential pseudorandom number generators rely on good multipliers, th...
research
01/30/2020

The time-adaptive statistical testing for random number generators

The problem of constructing effective statistical tests for random numbe...
research
05/03/2018

Scrambled Linear Pseudorandom Number Generators

Linear pseudorandom number generators are very popular due to their high...
research
11/01/2018

Quasi-random number generators for multivariate distributions based on generative neural networks

Generative moment matching networks are introduced as quasi-random numbe...
research
08/25/2022

A universal whitening algorithm for commercial random number generators

Random number generators are imperfect due to manufacturing bias and tec...
research
08/30/2021

A New Test for Hamming-Weight Dependencies

We describe a new statistical test for pseudorandom number generators (P...

Please sign up or login with your details

Forgot password? Click here to reset