Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
An Evolutionary Approach for Neural Networks and Fuzzy Systems
Authors: Melin, Patricia, Castillo, Oscar
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- About this book
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This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems. Hybrid intelligent systems can have different architectures, which have an impact on the efficiency and accuracy of pattern recognition systems, to achieve the ultimate goal of pattern recognition. This book also shows results of the application of hybrid intelligent systems to real-world problems of face, fingerprint, and voice recognition. This monograph is intended to be a major reference for scientists and engineers applying new computational and mathematical tools to intelligent pattern recognition and can be also used as a textbook for graduate courses in soft computing, intelligent pattern recognition, computer vision, or applied artificial intelligence.
- Table of contents (12 chapters)
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Introduction to Pattern Recognition with Intelligent Systems
Pages 1-5
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Type-1 Fuzzy Logic
Pages 7-32
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Intuitionistic and Type-2 Fuzzy Logic
Pages 33-53
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Supervised Learning Neural Networks
Pages 55-83
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Unsupervised Learning Neural Networks
Pages 85-107
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Table of contents (12 chapters)
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Bibliographic Information
- Bibliographic Information
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- Book Title
- Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
- Book Subtitle
- An Evolutionary Approach for Neural Networks and Fuzzy Systems
- Authors
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- Patricia Melin
- Oscar Castillo
- Series Title
- Studies in Fuzziness and Soft Computing
- Series Volume
- 172
- Copyright
- 2005
- Publisher
- Springer-Verlag Berlin Heidelberg
- Copyright Holder
- Springer-Verlag Berlin Heidelberg
- eBook ISBN
- 978-3-540-32378-5
- DOI
- 10.1007/b97585
- Hardcover ISBN
- 978-3-540-24121-8
- Softcover ISBN
- 978-3-642-06325-1
- Series ISSN
- 1434-9922
- Edition Number
- 1
- Number of Pages
- XIV, 272
- Topics
