About this product

Product Identifiers

PublisherSpringer

ISBN-100792395727

ISBN-139780792395720

eBay Product ID (ePID)192658

Product Key Features

Number of PagesXii, 209 Pages

Publication NameUniform Random Numbers : Theory and Practice

LanguageEnglish

Publication Year1995

SubjectProbability & Statistics / Stochastic Processes, Number Theory, System Theory, Optimization

TypeTextbook

AuthorShu Tezuka

Subject AreaMathematics, Science

SeriesThe Springer International Series in Engineering and Computer Science Ser.

FormatHardcover

Dimensions

Item Weight38.8 Oz

Item Length9.3 in

Item Width6.1 in

Additional Product Features

Intended AudienceScholarly & Professional

LCCN95-010562

Dewey Edition20

Series Volume Number315

Number of Volumes1 vol.

IllustratedYes

Dewey Decimal512/.76

Table Of Content1 Introduction.- 2 Preliminaries from Number Theory.- 3 Linear Congruential Generators.- 4 Beyond Linear Congruential Generators.- 5 Statistical Tests.- 6 Derandomization.- A Sample C Routines.- References.

SynopsisIn earlier forewords to the books in this series on Discrete Event Dynamic Systems (DEDS), we have dwelt on the pervasive nature of DEDS in our human-made world. From manufacturing plants to computer/communication networks, from traffic systems to command-and-control, modern civilization cannot function without the smooth operation of such systems. Yet mathemat ical tools for the analysis and synthesis of DEDS are nascent when compared to the well developed machinery of the continuous variable dynamic systems char acterized by differential equations. The performance evaluation tool of choice for DEDS is discrete event simulation both on account of its generality and its explicit incorporation of randomness. As it is well known to students of simulation, the heart of the random event simulation is the uniform random number generator. Not so well known to the practitioners are the philosophical and mathematical bases of generating "random" number sequence from deterministic algorithms. This editor can still recall his own painful introduction to the issues during the early 80's when he attempted to do the first perturbation analysis (PA) experiments on a per sonal computer which, unbeknownst to him, had a random number generator with a period of only 32,768 numbers. It is no exaggeration to say that the development of PA was derailed for some time due to this ignorance of the fundamentals of random number generation., In earlier forewords to the books in this series on Discrete Event Dynamic Systems (DEDS), we have dwelt on the pervasive nature of DEDS in our human-made world. From manufacturing plants to computer/communication networks, from traffic systems to command-and-control, modern civilization cannot function without the smooth operation of such systems. Yet mathemat- ical tools for the analysis and synthesis of DEDS are nascent when compared to the well developed machinery of the continuous variable dynamic systems char- acterized by differential equations. The performance evaluation tool of choice for DEDS is discrete event simulation both on account of its generality and its explicit incorporation of randomness. As it is well known to students of simulation, the heart of the random event simulation is the uniform random number generator. Not so well known to the practitioners are the philosophical and mathematical bases of generating "random" number sequence from deterministic algorithms. This editor can still recall his own painful introduction to the issues during the early 80's when he attempted to do the first perturbation analysis (PA) experiments on a per- sonal computer which, unbeknownst to him, had a random number generator with a period of only 32,768 numbers. It is no exaggeration to say that the development of PA was derailed for some time due to this ignorance of the fundamentals of random number generation.

LC Classification NumberQA402.5-402.6