Towards Neural-Based Understanding of the Cauchy Deviate Method for Processing Interval and Fuzzy Uncertainty

Authors

Vladik Kreinovich, The University of Texas at El PasoFollow
Hung T. Nguyen

Publication Date

1-2009

Comments

Technical Report: UTEP-CS-09-07a

Published in Proceedings of the 2009 World Congress of the International Fuzzy Systems Association IFSA, Lisbon, Portugal, July 20-24, 2009, pp. 1264-1269.

Abstract

One of the most efficient techniques for processing interval and fuzzy data is a Monte-Carlo type technique of Cauchy deviates that uses Cauchy distributions. This technique is mathematically valid, but somewhat counterintuitive. In this paper, following the ideas of Paul Werbos, we provide a natural neural network explanation for this technique.