Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing
An Evolutionary Approach for Neural Networks and Fuzzy Systems
Series: Studies in Fuzziness and Soft Computing; 172;
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45 385 Ft (43 223 Ft + 5% VAT)
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45 385 Ft
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
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Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number Softcover reprint of hardcover 1st ed. 2005
- Publisher Springer
- Date of Publication 30 November 2010
- Number of Volumes 1 pieces, Previously published in hardcover
- ISBN 9783642063251
- Binding Paperback
- No. of pages272 pages
- Size 235x155 mm
- Weight 454 g
- Language English
- Illustrations XIV, 272 p. Illustrations, black & white 0
Categories
Short description:
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.
MoreLong description:
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.
MoreTable of Contents:
Introduction to Pattern Recognition with Intelligent Systems.- Type-1 Fuzzy Logic.- Type-2 Fuzzy Logic and Intuitionistic Fuzzy Logic.- Supervised Neural Networks.- Unsupervised Neural Networks.- Modular Neural Networks.- Evolutionary Computing for Architecture Optimization.- Clustering with Intelligent Techniques.- Face Recognition with Modular Neural Networks and Fuzzy Measures.- Fingerprint Recognition with Modular Neural Networks and Fuzzy Measures.- Voice Recognition with Neural Networks and Genetic Algorithms.- Human Recognition Using Face, Fingerprint and Voice.
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