Introduction to Type-2 Fuzzy Logic in Neural Pattern Recognition Systems

  • Patricia Melin
Part of the Studies in Computational Intelligence book series (SCI, volume 389)

Abstract

We describe in this book, new methods for building intelligent systems for pattern recognition using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems [37, 57]. In this book, we are extending the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic [12]. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each technique offers in solving pattern recognition problems [59].

Keywords

Genetic Algorithm Fuzzy Logic Fuzzy System Fuzzy Inference System Modular Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Patricia Melin

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