Pattern Recognition (Second Edition)

Author: Bian Zhaoqi
Publisher:
Publish Date: 2000-01-01
Features: This book can not only serve as a textbook for graduate students and senior undergraduate students in automation, computer science, and related fields at universities, but also be referenced by a broad range of scientists and engineers working in pattern recognition in fields such as computer information processing, automatic control, geophysics, and bioinformatics. It is a teaching material from the Department of Automation at Tsinghua University, primarily discussing statistical pattern recognition theory and methods. The edition includes Bayesian decision theory, linear and nonlinear discriminant functions, the nearest neighbor rule, empirical risk minimization, feature extraction and selection, as well as clustering analysis, and so on. Most chapters are accompanied by exercises, making it suitable for mathematics and self-study. The second edition has undergone significant revisions and additions based on the edition, incorporating content on artificial neural networks, fuzzy pattern recognition, simulated annealing, genetic algorithms, statistical learning theory, and support vector machines. It also introduces practical applications of pattern recognition in areas such as face recognition, speaker voice recognition, and character recognition.