Random Number Generators

  • Manfred R. Schroeder
Part of the Springer Series in Information Sciences book series (SSINF, volume 7)


In contemporary computation there is an almost unquenchable thirst for random numbers. One particularly intemperate class of customers is comprised of the diverse Monte Carlo methods.1 Or one may want to study a problem (or control a process) that depends on several parameters which one doesn’t know how to choose. In such cases random choices are often preferred, or simply convenient. Finally, in system analysis (including biological systems) random “noise” is often a preferred test signal. And, of course, random numbers are useful — to say the least — in cryptography.


Random Number Generator Secret Message Period Length Pseudorandom Sequence Geiger Counter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Manfred R. Schroeder
    • 1
    • 2
  1. 1.Drittes Physikalisches InstitutUniversität GöttingenGöttingenGermany
  2. 2.Bell LaboratoriesAcoustics Speech and Mechanics ResearchMurray HillUSA

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