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On the complexity of binary floating point pseudorandom generation

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  • Nekrutkin Vladimir

    (St.Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034, Russia)

Abstract

The paper is devoted to the complexity analysis of binary floating point pseudorandom generators. We start with a stochastic model of a “usual” pseudorandom generator (PRNG). Then integer outputs of this generator are transformed into i.i.d. random variables, agreed with an abstract binary floating point system. Additionally, these random variables are approximately uniformly distributed on the interval [0,1]. Therefore, they can interpreted as (random) outputs of a binary floating point pseudorandom generator (flPRNG). The simulation complexity of such a transformation is defined as the average number of PRNG's outputs necessary to produce the unique output of flPRNG. Several transformations with minimal or approximately minimal complexities are presented and discussed.

Suggested Citation

  • Nekrutkin Vladimir, 2016. "On the complexity of binary floating point pseudorandom generation," Monte Carlo Methods and Applications, De Gruyter, vol. 22(2), pages 109-116, June.
    • Handle: RePEc:bpj:mcmeap:v:22:y:2016:i:2:p:109-116:n:2
    DOI: 10.1515/mcma-2016-0105
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    References listed on IDEAS

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    1. Romik, Dan, 1999. "Sharp entropy bounds for discrete statistical simulation," Statistics & Probability Letters, Elsevier, vol. 42(3), pages 219-227, April.
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