Computational Intelligence and Neuroscience 
Volume 2008 (2008), Article ID 426080, 8 pages
doi:10.1155/2008/426080
Research Article

Asymmetric Variate Generation via a Parameterless Dual Neural Learning Algorithm

Simone Fiori

 Dipartimento di Elettronica, Intelligenza Artificiale e Telecomunicazioni (DEIT), Università Politecnica delle Marche Via Brecce Bianche, Ancona I-60131, Italy
Received 16 June 2007; Accepted 19 September 2007

Recommended by S. Cruces-Alvarez

Abstract

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.