Quantifiers for randomness of chaotic pseudo random number generators

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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 impleme...

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Autores principales: De Micco, L., Larrondo, Hilda A., Plastino, Ángel Ricardo, Rosso, Osvaldo A.
Formato: Articulo
Lenguaje:Inglés
Publicado: 2009
Materias:
Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/127088
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-127088
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
spellingShingle Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
De Micco, L.
Larrondo, Hilda A.
Plastino, Ángel Ricardo
Rosso, Osvaldo A.
Quantifiers for randomness of chaotic pseudo random number generators
topic_facet Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
description 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.
format Articulo
Articulo
author De Micco, L.
Larrondo, Hilda A.
Plastino, Ángel Ricardo
Rosso, Osvaldo A.
author_facet De Micco, L.
Larrondo, Hilda A.
Plastino, Ángel Ricardo
Rosso, Osvaldo A.
author_sort De Micco, L.
title Quantifiers for randomness of chaotic pseudo random number generators
title_short Quantifiers for randomness of chaotic pseudo random number generators
title_full Quantifiers for randomness of chaotic pseudo random number generators
title_fullStr Quantifiers for randomness of chaotic pseudo random number generators
title_full_unstemmed Quantifiers for randomness of chaotic pseudo random number generators
title_sort quantifiers for randomness of chaotic pseudo random number generators
publishDate 2009
url http://sedici.unlp.edu.ar/handle/10915/127088
work_keys_str_mv AT demiccol quantifiersforrandomnessofchaoticpseudorandomnumbergenerators
AT larrondohildaa quantifiersforrandomnessofchaoticpseudorandomnumbergenerators
AT plastinoangelricardo quantifiersforrandomnessofchaoticpseudorandomnumbergenerators
AT rossoosvaldoa quantifiersforrandomnessofchaoticpseudorandomnumbergenerators
bdutipo_str Repositorios
_version_ 1764820451268231168

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