@article {10.3844/jcssp.2020.1.13,
article_type = {journal},
title = {Twister Generator of Random Normal Numbers by Box-Muller Model},
author = {Deon, Aleksei F. and Menyaev, Yulian A.},
volume = {16},
number = {1},
year = {2020},
month = {Jan},
pages = {1-13},
doi = {10.3844/jcssp.2020.1.13},
url = {https://thescipub.com/abstract/jcssp.2020.1.13},
abstract = {Twisting generators of the pseudorandom normal variables can use uniform random sequences as a basis. However, such technique could provide poor quality result in cases where the original sequences have insufficient uniformity or skipping of random values. This work offers a new approach for creating the random normal variables using the Box-Muller model as a basis together with the twisting generator of uniform planes. The simulation results confirm that the random variables obtained have a better approximation to normal Gaussian distribution. Moreover, combining this new approach with the tuning algorithm of basic twisting generation allows for a significantly increased the length of created sequences without using any additional random access memory of the computer.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}