Article thumbnail
Location of Repository

A Control Theory Formulation For Random Variate Generation

By Malik Magdon-Ismail Malik and Amir F. Atiya

Abstract

. The need to simulate complex systems in a Monte Carlo manner necessitates efficient methods for generating random variates. In this paper we propose a new method for random variate generation. The method is based on a contol-theory formulation. We use a cascade structure consisting of a neural network "controller " and a density estimator ("plant"). The neural network "controller" acts as a density shaper, and is trained until the density of its output (as measured by the density estimator) is as close as possible to the given density. Once training is complete in the design phase, the generation of random numbers can be performed in a very fast manner

Year: 2007
OAI identifier: oai:CiteSeerX.psu:10.1.1.21.1597
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.cs.rpi.edu/~magdon/... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.