Type-2 Fuzzy Logic: Theory and Applications

Oscar Castillo, Patricia Melin (Autoren)

Buch | Softcover

XIV, 246 Seiten

2010 | Softcover reprint of hardcover 1st ed. 2008
Springer Berlin (Verlag)
978-3-642-09513-9 (ISBN)

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We describe in this book, new methods for building intelligent systems 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. In this book, we are extending the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each te- nique offers. We consider in this book the use of type-2 fuzzy logic and traditional SC techniques to solve pattern recognition problems in real-world applications. We c- sider in particular the problems of face, fingerprint and voice recognition. We also consider the problem of recognizing a person by integrating the information given by the face, fingerprint and voice of the person. Other types of applications solved with type-2 fuzzy logic and SC techniques, include intelligent control, intelligent manuf- turing, and adaptive noise cancellation. This book is intended to be a major reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation.

1 Introduction to Type-2 Fuzzy Logic.- 2 Type-1 Fuzzy Logic.- 3 Type-2 Fuzzy Logic.- 4 A Method for Type-2 Fuzzy Inference in Control Applications.- 5 Design of Intelligent Systems with Interval Type-2 Fuzzy Logic.- 6 Method for Response Integration in Modular Neural Networks with Type-2 Fuzzy Logic.- 7 Type-2 Fuzzy Logic for Improving Training Data and Response Integration in Modular Neural Networks for Image Recognition.- 8 Fuzzy Inference Systems Type-1 and Type-2 for Digital Images Edge Detection.- 9 Systematic Design of a Stable Type-2 Fuzzy Logic Controller.- 10 Experimental Study of Intelligent Controllers Under Uncertainty Using Type-1 and Type-2 Fuzzy Logic.- 11 Evolutionary Optimization of Interval Type-2 Membership Functions Using the Human Evolutionary Model.- 12 Design of Fuzzy Inference Systems with the Interval Type-2 Fuzzy Logic Toolbox.- 13 Intelligent Control of the Pendubot with Interval Type-2 Fuzzy Logic.- 14 Automated Quality Control in Sound Speakers Manufacturing Using a Hybrid Neuro-fuzzy-Fractal Approach.- 15 A New Approach for Plant Monitoring Using Type-2 Fuzzy Logic and Fractal Theory.- 16 Intelligent Control of Autonomous Robotic Systems Using Interval Type-2 Fuzzy Logic and Genetic Algorithms.- 17 Adaptive Noise Cancellation Using Type-2 Fuzzy Logic and Neural Networks.

From the reviews:

"This research monograph offers a broad coverage of the recent developments in ... type-2 fuzzy sets and fuzzy systems. ... The monograph is arranged into 17 concise and well-focused chapters covering a wealth of applications and methodologies of type-2 fuzzy sets. ... chapters brings some useful motivating notes and elaborates on the algorithms pertinent to the problem at hand. ... a timely compendium of applications of type-2 fuzzy systems and offers the reader a sound overview of design techniques supporting the construction of such architectures." (Witold Pedrycz, Zentralblatt MATH, Vol. 1171, 2009)

Erscheint lt. Verlag	21.10.2010
Reihe/Serie	Studies in Fuzziness and Soft Computing
Zusatzinfo	XIV, 244 p. 188 illus.
Verlagsort	Berlin
Sprache	englisch
Maße	155 x 235 mm
Gewicht	393 g
Themenwelt	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Mathematik / Informatik ► Mathematik ► Allgemeines / Lexika
	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
	Mathematik / Informatik ► Mathematik ► Logik / Mengenlehre
	Technik
Schlagworte	algorithm • algorithms • Artificial Intelligence • Automation • autonomous robot • computer vision • fuzzy • Fuzzy Logic • Genetic algorithms • Model • Optimization • proving • robot • Type-2 Fuzzy Logic • Uncertainty
ISBN-10	3-642-09513-5 / 3642095135
ISBN-13	978-3-642-09513-9 / 9783642095139
Zustand	Neuware