Asymmetric Variate Generation via a Parameterless Dual Neural Learning Algorithm

In a previous work (S. Fiori, 2006), we proposed a random number generator based on a tunable non-linear neural system, whose learning rule is designed on the basis of a cardinal equation from statistics and whose implementation is based on look-up tables (LUTs). The aim of the present manuscript is...

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Bibliographic Details
Published inComputational Intelligence and Neuroscience Vol. 2008; no. 2008; pp. 38 - 45
Main Author Fiori, Simone
Format Journal Article
LanguageEnglish
Published Cairo, Egypt Hindawi Limiteds 2008
Hindawi Puplishing Corporation
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Subjects
Algorithms
Computer science
Experiments
Generators
Methods
Probability distribution
Studies
Online AccessGet full text
ISSN1687-5265
1687-5273
1687-5273
DOI10.1155/2008/426080

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Summary:In a previous work (S. Fiori, 2006), we proposed a random number generator based on a tunable non-linear neural system, whose learning rule is designed on the basis of a cardinal equation from statistics and whose implementation is based on look-up tables (LUTs). The aim of the present manuscript is to improve the above-mentioned random number generation method by changing the learning principle, while retaining the efficient LUT-based implementation. The new method proposed here proves easier to implement and relaxes some previous limitations.
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Recommended by S. Cruces-Alvarez
ISSN:1687-5265
1687-5273
1687-5273
DOI:10.1155/2008/426080