Identification of T-S fuzzy classifier via linear matrix inequalities

Moon Hwan Kim, Jin Bae Park, Weon Goo Kim, Young Hoon Joo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper a new linear matrix inequality (LMI) based design method for T-S fuzzy classifier is proposed. The various design factors including structure of fuzzy rule and various parameters should be considered to design T-S fuzzy classifier. To determine these design factors, we describe a new and efficient two-step approach that leads to good results for classification problem. At first, LMI based fuzzy clustering is applied to obtain compact fuzzy sets in antecedent. Then consequent parameters are optimized by a LMI optimization method.

Original languageEnglish
Title of host publicationAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings
PublisherSpringer Verlag
Pages1134-1137
Number of pages4
ISBN (Print)3540304622, 9783540304623
DOIs
Publication statusPublished - 2005
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 2005 Dec 52005 Dec 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
CountryAustralia
CitySydney
Period05/12/505/12/9

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kim, M. H., Park, J. B., Kim, W. G., & Joo, Y. H. (2005). Identification of T-S fuzzy classifier via linear matrix inequalities. In AI 2005: Advances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings (pp. 1134-1137). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3809 LNAI). Springer Verlag. https://doi.org/10.1007/11589990_155