Interval Type-2 Fuzzy Systems: Design Methods and Applications

  • Jerry M. Mendel


This chapter is the IT2 version of Chap.  4. It focuses first on what exactly “design of an IT2 fuzzy system” means, and then provides a tabular way for making the choices that are needed in order to fully specify an IT2 fuzzy system. It introduces two approaches to design, the partially dependent approach and the totally independent approach, but this time for singleton, T1 non-singleton and IT2 non-singleton IT2 fuzzy systems. It then describes the extension of the six design methods that were covered for type-1 fuzzy systems in Chap.  4 to IT2 fuzzy systems, namely: IT2 WM, least squares, derivative-based, SVD-QR, derivative-free, and iterative. It continues the three Chap.  4 case studies (forecasting of time series, knowledge mining using surveys, and fuzzy logic control), and continues the Chap.  4 applications of forecasting of compressed video traffic using IT2 Mamdani and TSK fuzzy systems, and IT2 rule-based classification of video traffic. The application of equalization of time-varying nonlinear digital communication channels is also covered. Thirteen examples are used to illustrate the important concepts.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.University of Southern CaliforniaLos AngelesUSA

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