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Download Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing) fb2, epub

by Oscar Castillo,Patricia Melin

Download Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing) fb2, epub

ISBN: 364206325X
Author: Oscar Castillo,Patricia Melin
Language: English
Publisher: Springer; Softcover reprint of hardcover 1st ed. 2005 edition (November 25, 2010)
Pages: 288
Category: Computer Science
Subcategory: IT
Rating: 4.3
Votes: 546
Size Fb2: 1455 kb
Size ePub: 1887 kb
Size Djvu: 1352 kb
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Hybrid intelligent systems that combine several soft computing techniques are needed due to the . Studies in Fuzziness and Soft Computing. Introduction to Pattern Recognition with Intelligent Systems. Pages 1-5. Melin, Professor Patricia (et a.

Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition. Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing. An Evolutionary Approach for Neural Networks and Fuzzy Systems. Authors: Melin, Patricia, Castillo, Oscar. eBook 118,99 €. price for Russian Federation (gross). ISBN 978-3-540-32378-5.

Soft Computing for Information Prodessing and Analysis, 2005 ISBN .

Soft Computing for Information Prodessing and Analysis, 2005 ISBN 3-540-22930-2. Vol. 172. Patricia Melin, Oscar Castillo Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing, 2005 ISBN 3-540-24121-3. Patricia Melin Oscar Castillo. 9 a new approach for face recognition using modular neural networks with a fuzzy logic method for response integration. We describe a new architecture for modular neural networks for achieving pattern recognition in the particular case of human faces. Also, the method for achieving response integration is based on the fuzzy Sugeno integral.

Studies in Fuzziness and Soft Computing.

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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.

Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. There are theoretical aspects as well as application papers. New methods and applications of hybrid intelligent systems using soft computing techniques are described. The book is organized in five main parts, which contain a group of papers around a similar subject.

Start by marking Hybrid Intelligent Systems for Pattern Recognition .

Start by marking Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems as Want to Read: Want to Read savin. ant to Read. Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems (Studies in Fuzziness and Soft Computing).

Bart Kosko, Neural networks and fuzzy systems: a dynamical systems .

Bart Kosko, Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence, Prentice-Hall, In. Upper Saddle River, NJ, 1991. 10. Langavi, R. and Berenji, . Fuzzy logic Fuzzylogic controller. In Proceedings of the second international conference on Fuzy Systems (FUZZ-IEEE '93) (MAR. 28-April. Sankar K. Pal, Soft Computing Pattern Recognition: Principles, Integrations, and Data Mining, Proceedings of the Joint JSAI 2001 Workshop on New Frontiers in Artificial Intelligence, . 61-271, January 2001.

Описание: Fuzzy systems, neural networks and evolutionary computation, considered as related to AI, combine flexibility and robustness, and are now widely used to build intelligent systems. This book covers soft computing implementations of intelligent systems models.

This monograph describes new methods for intelligent pattern recognition using soft computing techniques . Studies in Fuzziness and Soft Computing, 172.

This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms Full description Studies in Fuzziness and Soft Computing, 172. Subjects: Computer science.

Castillo, P. Melin, Hybrid intelligent systems for time series prediction using neural networks, fuzzy logic and fractal theory, IEEE Transactions on Neural Networks, vol. 13, no. 6, 2002. P. Melin, O. Castillo, Hybrid Intelligent Systems for Pattern Recognition using Soft Computing: An Evolutionary Approach for Neural Networks and Fuzzy Systems, Springer, 2005. Язык: b/d. Подтвердить.

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.

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