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181214 ||| eng |
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|a 978-1-5015-1513-2
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100 |
1 |
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|a Johnston, David
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245 |
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|a Random number generators - principles and practices
|h Elektronische Ressource
|b a guide for engineers and programmers
|c David Johnston
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260 |
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|a Berlin ; Boston
|b De Gruyter
|c 2018
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300 |
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|a XV, 424 Seiten
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|a Frontmatter -- About De/G PRESS -- Contents -- Preface -- 1. Introduction -- 2. Entropy Sources -- 3. Entropy Extraction -- 4. Cryptographically Secure Pseudorandom Number Generators -- 5. Nondeterministic Random Number Generators -- 6. Statistically Uniform Noncryptographic PRNGs -- 7. Gaussian or Normally Distributed PRNGs -- 8. Testing Random Numbers -- 9. Online Random Number Testing -- 10. SP800-22 Distinguishability Tests -- 11. Software Tools -- 12. RdRand and RdSeed Instructions in x86 CPUs -- 13. Accessing RNGs from Software -- 14. Floating-Point Random Numbers -- 15. Making a Uniform Random Number Between Nonpower of Two Bounds -- 16. Generating Random Prime Numbers -- 17. Additive Distributions -- 18. Probability Distributions -- 19. Quantifying Entropy -- 20. Random Methods to Generate π -- Appendix A. Adaptive Proportion Test Cutoff Tables -- Appendix B. High-Precision Incomplete Beta Function Implementation -- Appendix C. Incomplete Gamma Function Implementation -- Appendix D. Software Tool Sources -- Appendix E. Listing Reference -- Bibliography -- Index
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653 |
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|a Informatik / Algorithmen
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653 |
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|a Computer Sciences / Algorithms
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653 |
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|a PRNG
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653 |
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|a Extractors
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653 |
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|a Mathematik / Numerik und wissenschaftliches Rechnen
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653 |
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|a Mathematics / Numerical and Computational Mathematics
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653 |
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|a Entropy
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653 |
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|a Randomness
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653 |
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|a RNG
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041 |
0 |
7 |
|a eng
|2 ISO 639-2
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989 |
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|b GRUYMPG
|a DeGruyter MPG Collection
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5 |
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|a 10.1515/9781501506062
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776 |
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|z 978-1-5015-0606-2
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776 |
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|z 978-1-5015-0626-0
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856 |
4 |
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|u https://www.degruyter.com/doi/book/10.1515/9781501506062
|x Verlag
|3 Volltext
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|a 510
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|a Random Number Generators, Principles and Practices has been written for programmers, hardware engineers, and sophisticated hobbyists interested in understanding random numbers generators and gaining the tools necessary to work with random number generators with confidence and knowledge. Using an approach that employs clear diagrams and running code examples rather than excessive mathematics, random number related topics such as entropy estimation, entropy extraction, entropy sources, PRNGs, randomness testing, distribution generation, and many others are exposed and demystified.
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