Quantifiers for randomness of chaotic pseudo-random number generators

En:

Philos. Trans. R. Soc. A Math. Phys. Eng. Sci. 2009;367(1901):3281-3296

Fecha:

2009

Formato:

application/pdf

Tipo de documento:

info:eu-repo/semantics/article
info:ar-repo/semantics/artículo
info:eu-repo/semantics/publishedVersion

Descriptores:

Excess entropy -  Permutation entropy -  Random number -  Rate entropy -  Recurrence plots -  Statistical complexity -  Chaotic systems -  Entropy -  Number theory

Descripción:

We deal with randomness quantifiers and concentrate on their ability to discern the hallmark of chaos in time series used in connection with pseudo-random number generators (PRNGs). Workers in the field are motivated to use chaotic maps for generating PRNGs because of the simplicity of their implementation. Although there exist very efficient general-purpose benchmarks for testing PRNGs, we feel that the analysis provided here sheds additional didactic light on the importance of the main statistical characteristics of a chaotic map, namely (i) its invariant measure and (ii) the mixing constant. This is of help in answering two questions that arise in applications: (i) which is the best PRNG among the available ones? and (ii) if a given PRNG turns out not to be good enough and a randomization procedure must still be applied to it, which is the best applicable randomization procedure? Our answer provides a comparative analysis of several quantifiers advanced in the extant literature. © 2009 The Royal Society.

Identificador(es):

http://hdl.handle.net/20.500.12110/paper_1364503X_v367_n1901_p3281_DeMicco

Derechos:

info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/2.5/ar