Pattern recognition /
Sergios Theodoridis, Konstantinos Koutroumbas.
- 4th ed.
- Amsterdam ; London : Elsevier/Academic Press, c2009.
- a xvii, 961 p. : ill. ; 25 cm.
Previous ed.: Amsterdam: Academic, 2003.
Includes bibliographical references and index.
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.
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.