Полное факториальное моделирование равномерных последовательностей целых случайных величин

Полное факториальное моделирование равномерных последовательностей…

ISSN 0236-3933. Вестник МГТУ им. Н.Э. Баумана. Сер. Приборостроение. 2017. № 5

147

Просьба ссылаться на эту статью следующим образом:

Деон А.Ф., Меняев Ю.А. Полное факториальное моделирование равномерных последо-

вательностей целых случайных величин // Вестник МГТУ им. Н.Э. Баумана. Сер. При-

боростроение. 2017. № 5. C. 132–149. DOI: 10.18698/0236-3933-2017-5-132-149

COMPLETE FACTORIAL SIMULATION OF INTEGER RANDOM NUMBER

UNIFORM SEQUENCES

A.F. Deon

deonalex@mail.ru

Yu.A. Menyaev

yamenyaev@uams.edu

Bauman Moscow State Technical University, Moscow, Russian Federation

Winthrop P. Rockefeller Cancer Institute, Little Rock, USA

Abstract

Keywords

Random sequences are widely used in theoretical and

practical areas of interests in human and technical activi-

ties. An important part of these fields refers to the proce-

dures of producing stochastic values. One direction adapts

the sequenced generation of pseudorandom numbers and

the other direction uses a complete set of all stochastic

sequences. The first direction is well studied and traditio-

nally applied in varies areas ranging from cryptography

and technical systems to medical and biological trials. The

second direction generally uses systems for preliminary

universal testing. In this paper, we follow the second direc-

tion, where the underlying approaches in modern genera-

tors of random numbers are considered. In some of the

modern random numbers generators the skipping and

repeating random values may be found. We have formed

the requirements that if followed help to solve the prob-

lems of skipping and repeating. Moreover, we propose

novel algorithms based on factorial expansion which pro-

vide fast generation of such sequences. Finally, we describe

advantages and disadvantages of findings of our research

Computer simulation, random

number generator, stochastic

sequences algorithm

Received 29.06.2017

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Available at:

http://dl.acm.org/citation.cfm?doid=1389095.1389437