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| PATTERN RECOGNITION
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To order this title, and for more information, click here
Fourth Edition
By
Sergios Theodoridis, Department of Informatics and Telecommunications, University of Athens, Greece
Konstantinos Koutroumbas, Institute for Space Applications & Remote Sensing, National Observatory of Athens, Greece
Description
This book considers classical and current theory and practice, of supervised, unsupervised and semi-supervised pattern recognition,
to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition,
have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated
in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback.
Audience
Signal processing, computing and applied mathematics students taking graduate courses on pattern recognition and machine learning. R&D
engineers in image and signal processing; university researchers in image and signal processing
Contents
1. Introduction
2. Classifiers based on Bayes Decision
3. Linear Classifiers
4. Nonlinear Classifiers
5. Feature Selection
6. Feature
Generation I: Data Transformation and Dimensionality Reduction
7. Feature Generation II
8. Template Matching
9. Context Depedant Clarification
10. System Evaultion
11. Clustering: Basic Concepts
12. Clustering Algorithms: Algorithms L Sequential
13. Clustering Algorithms
II: Hierarchical
14. Clustering Algorithms III: Based on Function Optimization
15. Clustering Algorithms IV: Clustering
16. Cluster
Validity
| Bibliographic details |
Hardbound, 984 pages, publication date: OCT-2008
ISBN-13: 978-1-59749-272-0
Imprint: ACADEMIC PRESS
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| Price and Ordering |
Price:
GBP 49.99
USD 99.95
EUR 58.95
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Last update: 26 Oct 2009
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