Systems identification using type-2 fuzzy neural network (type-2 FNN) systems

Ching Hung Lee, Yu Ching Lin, Wei Yu Lai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

50 Scopus citations

Abstract

This paper presents a type-2 fuzzy neural network system (type-2 FNN) and its learning algorithm using back-propagation algorithm. In our previous results, the FNN system using type-1 fuzzy logic systems (FLS) is called type-1 FNN system. It has the properties of parallel computation scheme, easy to implement, fuzzy logic inference system, and parameters convergence. For considering the fuzzy rules uncertainties, we use the type-2 FLSs to develop a type-2 FNN system. The type-2 fuzzy sets let us model and minimize the effects of uncertainties in rule-based fuzzy logic systems (FLSs). In this paper, the previous results of type-1 FNN are extended to a type-2 one. In addition, the corresponding learning algorithm is derived by back-program algorithm. Several examples are presented to illustrate the effectiveness of our approach.

Original languageEnglish
Title of host publicationProceedings - 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation
Subtitle of host publicationComputational Intelligence in Robotics and Automation for the New Millennium
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1264-1269
Number of pages6
ISBN (Electronic)0780378660
DOIs
StatePublished - 2003
Event2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003 - Kobe, Japan
Duration: 16 Jul 200320 Jul 2003

Publication series

NameProceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA
Volume3

Conference

Conference2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA 2003
CountryJapan
CityKobe
Period16/07/0320/07/03

Keywords

  • fuzzy neural network
  • type-2 fuzzy sets back-propagation algorithm

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