Quantifiers for randomness of chaotic pseudo random number generators

Autores
De Micco, L.; Larrondo, Hilda A.; Plastino, Ángel Ricardo; Rosso, Osvaldo A.
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
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.
Instituto de Física La Plata
Materia
Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/127088

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spelling Quantifiers for randomness of chaotic pseudo random number generatorsDe Micco, L.Larrondo, Hilda A.Plastino, Ángel RicardoRosso, Osvaldo A.FísicaRandom numberStatistical complexityRecurrence plotsRate entropyExcess entropyPermutation entropyWe 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.Instituto de Física La Plata2009-08-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf3281-3296http://sedici.unlp.edu.ar/handle/10915/127088enginfo:eu-repo/semantics/altIdentifier/issn/1364-503Xinfo:eu-repo/semantics/altIdentifier/arxiv/0812.2250info:eu-repo/semantics/altIdentifier/pmid/19620124info:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2009.0075info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:30:42Zoai:sedici.unlp.edu.ar:10915/127088Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:30:43.069SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Quantifiers for randomness of chaotic pseudo random number generators
title Quantifiers for randomness of chaotic pseudo random number generators
spellingShingle Quantifiers for randomness of chaotic pseudo random number generators
De Micco, L.
Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
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
dc.creator.none.fl_str_mv De Micco, L.
Larrondo, Hilda A.
Plastino, Ángel Ricardo
Rosso, Osvaldo A.
author De Micco, L.
author_facet De Micco, L.
Larrondo, Hilda A.
Plastino, Ángel Ricardo
Rosso, Osvaldo A.
author_role author
author2 Larrondo, Hilda A.
Plastino, Ángel Ricardo
Rosso, Osvaldo A.
author2_role author
author
author
dc.subject.none.fl_str_mv Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
topic Física
Random number
Statistical complexity
Recurrence plots
Rate entropy
Excess entropy
Permutation entropy
dc.description.none.fl_txt_mv 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.
Instituto de Física La Plata
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.
publishDate 2009
dc.date.none.fl_str_mv 2009-08-28
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/127088
url http://sedici.unlp.edu.ar/handle/10915/127088
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/1364-503X
info:eu-repo/semantics/altIdentifier/arxiv/0812.2250
info:eu-repo/semantics/altIdentifier/pmid/19620124
info:eu-repo/semantics/altIdentifier/doi/10.1098/rsta.2009.0075
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
3281-3296
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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