Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)

In many practical applications, it turns out to be useful to use the notion of fuzzy transform: once we have functions A1(x)≥0,...,An≥0, with ∑i=1nAi(x)=1, we can then represent each function f(x) by the coefficients Fi=(∫f(x)⋅Ai(x)dx)/(∫Ai(x)dx). Once we know the coefficients Fi, we can (approximat...

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Main Authors: Irina Perfilieva, Vladik Kreinovich
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Advances in Fuzzy Systems
Online Access:http://dx.doi.org/10.1155/2011/719256
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spelling doaj-8ecacbc403e34fa4b5b7b7855958286c2020-11-24T22:38:07ZengHindawi LimitedAdvances in Fuzzy Systems1687-71011687-711X2011-01-01201110.1155/2011/719256719256Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)Irina Perfilieva0Vladik Kreinovich1Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, 701 03 Ostrava, Czech RepublicDepartment of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USAIn many practical applications, it turns out to be useful to use the notion of fuzzy transform: once we have functions A1(x)≥0,...,An≥0, with ∑i=1nAi(x)=1, we can then represent each function f(x) by the coefficients Fi=(∫f(x)⋅Ai(x)dx)/(∫Ai(x)dx). Once we know the coefficients Fi, we can (approximately) reconstruct the original function f(x) as ∑i=1nFi⋅Ai(x). The original motivation for this transformation came from fuzzy modeling, but the transformation itself is a purely mathematical transformation. Thus, the empirical successes of this transformation suggest that this transformation can be also interpreted in more traditional (nonfuzzy) mathematics as well. Such an interpretation is presented in this paper. Specifically, we show that the 2002 probabilistic interpretation of fuzzy modeling by Sánchez et al. can be modified into a natural probabilistic explanation of fuzzy transform formulas.http://dx.doi.org/10.1155/2011/719256
collection DOAJ
language English
format Article
sources DOAJ
author Irina Perfilieva
Vladik Kreinovich
spellingShingle Irina Perfilieva
Vladik Kreinovich
Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)
Advances in Fuzzy Systems
author_facet Irina Perfilieva
Vladik Kreinovich
author_sort Irina Perfilieva
title Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)
title_short Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)
title_full Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)
title_fullStr Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)
title_full_unstemmed Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)
title_sort towards an (even more) natural probabilistic interpretation of fuzzy transforms (and of fuzzy modeling)
publisher Hindawi Limited
series Advances in Fuzzy Systems
issn 1687-7101
1687-711X
publishDate 2011-01-01
description In many practical applications, it turns out to be useful to use the notion of fuzzy transform: once we have functions A1(x)≥0,...,An≥0, with ∑i=1nAi(x)=1, we can then represent each function f(x) by the coefficients Fi=(∫f(x)⋅Ai(x)dx)/(∫Ai(x)dx). Once we know the coefficients Fi, we can (approximately) reconstruct the original function f(x) as ∑i=1nFi⋅Ai(x). The original motivation for this transformation came from fuzzy modeling, but the transformation itself is a purely mathematical transformation. Thus, the empirical successes of this transformation suggest that this transformation can be also interpreted in more traditional (nonfuzzy) mathematics as well. Such an interpretation is presented in this paper. Specifically, we show that the 2002 probabilistic interpretation of fuzzy modeling by Sánchez et al. can be modified into a natural probabilistic explanation of fuzzy transform formulas.
url http://dx.doi.org/10.1155/2011/719256
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