A preliminary investigation of a linguistic perceptron

For many years, one of the problems in pattern recognition is classification. There are many methods proposed to deal with this type of problem. The data sets are sometimes in the binary form (real number) and represented by vectors of binary numbers (real numbers) although there are uncertainties i...

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Main Author: Auephanwiriyaku S.
Format: Conference or Workshop Item
Language:English
Published: 2014
Online Access:http://www.scopus.com/inward/record.url?eid=2-s2.0-33745585824&partnerID=40&md5=dc22de2fac12d50c51aabb1474353cbd
http://cmuir.cmu.ac.th/handle/6653943832/1267
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Institution: Chiang Mai University
Language: English
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spelling th-cmuir.6653943832-12672014-08-29T09:29:02Z A preliminary investigation of a linguistic perceptron Auephanwiriyaku S. For many years, one of the problems in pattern recognition is classification. There are many methods proposed to deal with this type of problem. The data sets are sometimes in the binary form (real number) and represented by vectors of binary numbers (real numbers) although there are uncertainties in the data. This study is concerned with a linguistic perceptron with vectors of fuzzy numbers as inputs. This algorithm is based on the extension principle and the decomposition theorem. A synthetic data set has been utilized to illustrate the behavior of this linguistic version of perceptron. We compare the result from the linguistic perceptron with that from the regular perceptron. © Springer-Verlag Berlin Heidelberg 2005. 2014-08-29T09:29:01Z 2014-08-29T09:29:01Z 2005 Conference Paper 3540304622; 9783540304623 03029743 10.1007/11589990_165 67429 http://www.scopus.com/inward/record.url?eid=2-s2.0-33745585824&partnerID=40&md5=dc22de2fac12d50c51aabb1474353cbd http://cmuir.cmu.ac.th/handle/6653943832/1267 English
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
language English
description For many years, one of the problems in pattern recognition is classification. There are many methods proposed to deal with this type of problem. The data sets are sometimes in the binary form (real number) and represented by vectors of binary numbers (real numbers) although there are uncertainties in the data. This study is concerned with a linguistic perceptron with vectors of fuzzy numbers as inputs. This algorithm is based on the extension principle and the decomposition theorem. A synthetic data set has been utilized to illustrate the behavior of this linguistic version of perceptron. We compare the result from the linguistic perceptron with that from the regular perceptron. © Springer-Verlag Berlin Heidelberg 2005.
format Conference or Workshop Item
author Auephanwiriyaku S.
spellingShingle Auephanwiriyaku S.
A preliminary investigation of a linguistic perceptron
author_facet Auephanwiriyaku S.
author_sort Auephanwiriyaku S.
title A preliminary investigation of a linguistic perceptron
title_short A preliminary investigation of a linguistic perceptron
title_full A preliminary investigation of a linguistic perceptron
title_fullStr A preliminary investigation of a linguistic perceptron
title_full_unstemmed A preliminary investigation of a linguistic perceptron
title_sort preliminary investigation of a linguistic perceptron
publishDate 2014
url http://www.scopus.com/inward/record.url?eid=2-s2.0-33745585824&partnerID=40&md5=dc22de2fac12d50c51aabb1474353cbd
http://cmuir.cmu.ac.th/handle/6653943832/1267
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