Pattern Recognition (English Version. 3rd Edition)

Author: (Greece) Theodoridis
Publisher:
Publish Date: 2006-09-01
Features: This book comprehensively integrates the classic and current theories and practices of supervised and unsupervised pattern recognition, establishing a complete foundational knowledge system for professional technicians and university students. Co-authored by two top experts in the field of pattern recognition, the book comprehensively elaborates on the applications of pattern recognition from an engineering perspective. The content includes Bayesian classification, Bayesian networks, linear and nonlinear classifiers (including neural networks and support vector machines), dynamic programming, and hidden Markov models for sequential data. It also covers features (including wavelets, principal component analysis, independent component analysis, and fractal analysis), feature selection techniques, fundamental concepts from learning theory, clustering concepts and algorithms, and more. This renowned global classic is both comprehensive and relatively independent, offering introductions to foundational knowledge, updates on current research in the field, and prospects for future developments. It is the most comprehensive reference book in the field, adopted by numerous universities worldwide as a textbook. This book can serve as a textbook for graduate students and senior undergraduate students in computer science, electronics, communications, automation, and related fields at universities, as well as a reference for engineers and technicians in fields such as computer information processing and automatic control.