Type-2 Fuzzy Logic : Theory and Applications (Studies in Fuzziness and Soft Computing) 〈Vol. 223〉

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Type-2 Fuzzy Logic : Theory and Applications (Studies in Fuzziness and Soft Computing) 〈Vol. 223〉

Castillo, O./ Melin, P.

ウェブストア価格 ¥24,623（本体¥22,385）
Springer（2008/02発売）
外貨定価 US$ 109.99
ポイント 223pt

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製本 Hardcover:ハードカバー版／ページ数 300 p.
言語 ENG
商品コード 9783540762836
DDC分類 621

Full Description

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.