Analyses of regular fuzzy neural networks for approximation capabilities
type: Item
instance of: scholarly article
title: Analyses of regular fuzzy neural networks for approximation capabilities
zbMATH Open document ID: 0966.93064
DOI: 10.1016/S0165-0114(98)00248-6
author: Pu-yin Liu
published in: Fuzzy Sets and Systems
publication date: 2001-02-06T00:00:00Z
review text: Regular fuzzy neural networks (RFNNs) are proved to be the universal approximator to extended functions. By defining the multivariable trapezoidal F functions with extended addition of F numbers it is shown that the above conclusions hold for RFNNs with multi-input unit.
reviewed by: Angela Slavova
Mathematics Subject Classification ID: 93C42
Mathematics Subject Classification ID: 41A99
Mathematics Subject Classification ID: 92B20
zbMATH DE Number: 1517231
zbMATH Keywords: fuzzy neural networks
zbMATH Keywords: universal approximation
zbMATH Keywords: trapezoidal F numbers
zbMATH Keywords: trapezoidal F function
MaRDI profile type: Publication
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description: scientific article; zbMATH DE number 1517231