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Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing

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Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing Synopsis

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.

About This Edition

ISBN: 9783642063251
Publication date:
Author: Patricia Melin, Oscar Castillo
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 272 pages
Series: Studies in Fuzziness and Soft Computing
Genres: Mathematical theory of computation
Pattern recognition
Automatic control engineering
Digital signal processing (DSP)
Artificial intelligence
Maths for engineers
Electronics engineering

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