Pattern Recognition (Second Edition)

Author: Theodoridis et al. [Greek]
Publisher:
Publish Date: 2004-08-01
Features: Pattern recognition emerged in the 1920s, and with the advent of computers in the 1940s and the rise of artificial intelligence in the 1950s, it rapidly developed into a discipline by the early 1960s. The theories and methods of pattern recognition have been successfully applied in many areas, from the initial optical character recognition (OCR) to pen-based computing, biometric identification, DNA sequence analysis, chemical odor recognition, drug molecule recognition, image understanding, face recognition, expression recognition, gesture recognition, speech recognition, speaker recognition, information retrieval, data mining, and signal processing, among others. However, compared to biological cognitive systems, the recognition capabilities and robustness of pattern recognition systems are still far from satisfactory. There are still many fundamental theories and basic methods in this field that need to be addressed, and new challenges continue to arise. For this reason, professionals in this field urgently need a high-level academic work that not only introduces the foundational knowledge but also covers the current state of research and future development prospects. This book is exactly such a classic work. It is based on the previous edition and was completed by two senior experts with over a decade of teaching experience. The book is divided into 16 chapters, primarily covering feature selection and feature generation, including wavelets, fractals, and independent component analysis; linear and nonlinear classifiers, such as Bayesian classification, multilayer perceptrons, decision trees, and RBF networks; context-related classification, including dynamic programming and hidden Markov model techniques; new chapters on support vector machines, variable pattern matching, and constrained optimization in the appendix; and applications such as image analysis, text recognition, medical diagnosis, and speech recognition. Additionally, each chapter includes exercises. This book can serve as a textbook for graduate students and senior undergraduate students in fields such as automation, computer science, electronics, and communications at universities, as well as a reference for engineers and technicians in related fields like computer information processing and automatic control.