Random Numbers and Computers

This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples. Random Numbers and Computers is an essential introduction or refresher on pseudorandom numbers in computer science.  The first comprehensive book on the topic, readers ar...

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Bibliographic Details
Main Author Kneusel, Ronald T
Format eBook Book
LanguageEnglish
Published Cham Springer Nature 2018
Springer
Springer International Publishing AG
Springer International Publishing
Edition1
Subjects
Algorithm Analysis and Problem Complexity
Algorithms
Computer programming, programs, data
Computer Science
Cryptology
Numeric Computing
Probability and Statistics in Computer Science
Random number generators
Online AccessGet full text
ISBN9783319776972
3319776975
9783319776965
3319776967
DOI10.1007/978-3-319-77697-2

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Abstract This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples. Random Numbers and Computers is an essential introduction or refresher on pseudorandom numbers in computer science.  The first comprehensive book on the topic, readers are provided with a practical introduction to the techniques of pseudorandom number generation, including how the algorithms work and how to test the output to decide if it is suitable for a particular purpose.    Practical applications are demonstrated with hands-on presentation and descriptions that readers can apply directly to their own work. Examples are in C and Python and given with an emphasis on understanding the algorithms to the point of practical application. The examples are meant to be implemented, experimented with and improved/adapted by the reader. 
AbstractList This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples. Random Numbers and Computers is an essential introduction or refresher on pseudorandom numbers in computer science.  The first comprehensive book on the topic, readers are provided with a practical introduction to the techniques of pseudorandom number generation, including how the algorithms work and how to test the output to decide if it is suitable for a particular purpose.    Practical applications are demonstrated with hands-on presentation and descriptions that readers can apply directly to their own work. Examples are in C and Python and given with an emphasis on understanding the algorithms to the point of practical application. The examples are meant to be implemented, experimented with and improved/adapted by the reader. 
Author Kneusel, Ronald T
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Snippet This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples. Random Numbers and Computers...
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SubjectTerms Algorithm Analysis and Problem Complexity
Algorithms
Computer programming, programs, data
Computer Science
Cryptology
Numeric Computing
Probability and Statistics in Computer Science
Random number generators
TableOfContents 6 Cryptographically Secure Pseudorandom Number Generators -- 6.1 Properties of Secure Generators -- 6.2 Blum Blum Shub -- 6.3 ISAAC -- 6.4 Fortuna -- 6.5 ChaCha20 -- 6.6 Chapter Summary -- Exercises -- References -- 7 Other Random Sequences -- 7.1 Introduction -- 7.2 Using Normal Numbers -- 7.3 Using Factorials -- 7.4 Using Cellular Automata -- 7.5 Using Chaotic Maps -- 7.6 An Experiment -- 7.7 Chapter Summary -- Exercises -- References -- Index
Intro -- Preface -- A Note About Terminology -- Who Should Read This Book -- How To Use This Book -- Acknowledgments -- Contents -- 1 Random and Pseudorandom Sequences -- 1.1 Random Sequences -- 1.2 Experiment: Humans Are Bad at Randomness -- 1.3 Pseudorandom Sequences -- 1.4 Experiment: Fractals and Good Versus Bad Pseudorandom Values -- 1.5 A CPU Hardware Generator -- 1.6 Chapter Summary -- Exercises -- References -- 2 Generating Uniform Random Numbers -- 2.1 Uniform Random Numbers -- 2.2 Linear Congruential Generators -- 2.3 Mersenne Twisters -- 2.4 Xorshift and Variants -- 2.5 Complimentary Multiply-with-Carry Generators -- 2.6 Counter-Based Generators -- 2.7 Combined Generators -- 2.8 Speed Tests -- 2.9 Quasirandom Generators -- 2.10 Chapter Summary -- Exercises -- References -- 3 Generating Nonuniform Random Numbers -- 3.1 Nonuniform Random Numbers -- 3.2 Normal Distribution -- 3.3 Binomial Distribution -- 3.4 Gamma and Beta Distributions -- 3.5 Exponential Distribution -- 3.6 Poisson Distribution -- 3.7 Chapter Summary -- Exercises -- References -- 4 Testing Pseudorandom Generators -- 4.1 Classical Randomness Tests -- 4.1.1 χ2 Test -- 4.1.2 Kolmogorov-Smirnov Test -- 4.1.3 Serial Test -- 4.1.4 Gap Test -- 4.1.5 Maximum-of-t Test -- 4.1.6 Serial Correlation Test -- 4.1.7 Permutation Test -- 4.1.8 Random Excursions Test -- 4.2 Applying the Classical Randomness Tests -- 4.3 Test Suite-Dieharder -- 4.4 Test Suite-TestU01 -- 4.5 Quick Randomness Tests-ent -- 4.6 Chapter Summary -- Exercises -- References -- 5 Parallel Random Number Generators -- 5.1 Methods for Generating and Testing Streams of Random Numbers -- 5.2 Per Stream Generators -- 5.3 Skipping -- 5.4 Random Seeding -- 5.5 Fog Method -- 5.6 Counter-Based Generators in Parallel -- 5.7 Discussion -- 5.8 Chapter Summary -- Exercises -- References
Title Random Numbers and Computers
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