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Unbiased Random Sequences from Quasigroup String Transformations

  • Smile Markovski
  • Danilo Gligoroski
  • Ljupco Kocarev
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3557)

Abstract

The need of true random number generators for many purposes (ranging from applications in cryptography and stochastic simulation, to search heuristics and game playing) is increasing every day. Many sources of randomness possess the property of stationarity. However, while a biased die may be a good source of entropy, many applications require input in the form of unbiased bits, rather than biased ones. In this paper, we present a new technique for simulating fair coin flips using a biased, stationary source of randomness. Moreover, the same technique can also be used to improve some of the properties of pseudo random number generators. In particular, an improved pseudo random number generator has almost unmeasurable period, uniform distribution of the letters, pairs of letters, triples of letters, and so on, and passes many statistical tests of randomness. Our algorithm for simulating fair coin flips using a biased, stationary source of randomness (or for improving the properties of pseudo random number generators) is designed by using quasigroup string transformations and its properties are mathematically provable. It is very flexible, the input/output strings can be of 2-bits letters, 4-bits letters, bytes, 2-bytes letters, and so on. It is of linear complexity and it needs less than 1Kb memory space in its 2-bits and 4-bits implementations, hence it is suitable for embedded systems as well.

Keywords

Transition Matrix Hash Function Random Number Generator Stationary Source Pseudo Random Number Generator 
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 2005

Authors and Affiliations

  • Smile Markovski
    • 1
  • Danilo Gligoroski
    • 1
  • Ljupco Kocarev
    • 2
  1. 1.Faculty of Natural Sciences and Mathematics, Institute of Informatics“Ss Cyril and Methodius” UniversitySkopjeRepublic of Macedonia
  2. 2.Institute for Nonlinear ScienceUniversity of California San DiegoLa JollaUSA

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