Intensive statistical complexity measure of pseudorandom number generators
A Statistical Complexity measure has been recently proposed to quantify the performance of chaotic Pseudorandom number generators (PRNG) (Physica A 354 (2005) 281). Here we revisit this quantifier and introduce two important improvements: (i) consideration of an intensive statistical complexity (Phy...
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Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v356_n1_p133_Larrondo http://hdl.handle.net/20.500.12110/paper_03784371_v356_n1_p133_Larrondo |
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paper:paper_03784371_v356_n1_p133_Larrondo2023-06-08T15:40:03Z Intensive statistical complexity measure of pseudorandom number generators Random number generators Statistical complexity Computational complexity Evaluation Mathematical techniques Probability density function Statistical methods Intensive statistical complexity Prescription Random number generators Statistical complexity Random number generation A Statistical Complexity measure has been recently proposed to quantify the performance of chaotic Pseudorandom number generators (PRNG) (Physica A 354 (2005) 281). Here we revisit this quantifier and introduce two important improvements: (i) consideration of an intensive statistical complexity (Physica A 334 (2004) 119), and (ii) following the prescription of Brand and Pompe (Phys. Rev. Lett. 88 (2002) 174102-1) in evaluating the probability distribution associated with the PRNG. The ensuing new measure is applied to a very well-tested PRNG advanced by Marsaglia. © 2005 Elsevier B.V. All rights reserved. 2005 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v356_n1_p133_Larrondo http://hdl.handle.net/20.500.12110/paper_03784371_v356_n1_p133_Larrondo |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
topic |
Random number generators Statistical complexity Computational complexity Evaluation Mathematical techniques Probability density function Statistical methods Intensive statistical complexity Prescription Random number generators Statistical complexity Random number generation |
spellingShingle |
Random number generators Statistical complexity Computational complexity Evaluation Mathematical techniques Probability density function Statistical methods Intensive statistical complexity Prescription Random number generators Statistical complexity Random number generation Intensive statistical complexity measure of pseudorandom number generators |
topic_facet |
Random number generators Statistical complexity Computational complexity Evaluation Mathematical techniques Probability density function Statistical methods Intensive statistical complexity Prescription Random number generators Statistical complexity Random number generation |
description |
A Statistical Complexity measure has been recently proposed to quantify the performance of chaotic Pseudorandom number generators (PRNG) (Physica A 354 (2005) 281). Here we revisit this quantifier and introduce two important improvements: (i) consideration of an intensive statistical complexity (Physica A 334 (2004) 119), and (ii) following the prescription of Brand and Pompe (Phys. Rev. Lett. 88 (2002) 174102-1) in evaluating the probability distribution associated with the PRNG. The ensuing new measure is applied to a very well-tested PRNG advanced by Marsaglia. © 2005 Elsevier B.V. All rights reserved. |
title |
Intensive statistical complexity measure of pseudorandom number generators |
title_short |
Intensive statistical complexity measure of pseudorandom number generators |
title_full |
Intensive statistical complexity measure of pseudorandom number generators |
title_fullStr |
Intensive statistical complexity measure of pseudorandom number generators |
title_full_unstemmed |
Intensive statistical complexity measure of pseudorandom number generators |
title_sort |
intensive statistical complexity measure of pseudorandom number generators |
publishDate |
2005 |
url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03784371_v356_n1_p133_Larrondo http://hdl.handle.net/20.500.12110/paper_03784371_v356_n1_p133_Larrondo |
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1768541657586728960 |