Type-2 Fuzzy Graphical Models for Pattern Recognition

✍ Scribed by Jia Zeng, Zhi-Qiang Liu (auth.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2015
• Tongue: English
• Leaves: 210
• Series: Studies in Computational Intelligence 591
• Edition: 1
• Category: Library

✦ Synopsis

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

✦ Table of Contents

Front Matter....Pages i-xiii
Introduction....Pages 1-7
Probabilistic Graphical Models....Pages 9-16
Type-2 Fuzzy Sets for Pattern Recognition....Pages 17-44
Type-2 Fuzzy Gaussian Mixture Models....Pages 45-56
Type-2 Fuzzy Hidden Moarkov Models....Pages 57-83
Type-2 Fuzzy Markov Random Fields....Pages 85-128
Type-2 Fuzzy Topic Models....Pages 129-198
Conclusions and Future Work....Pages 199-201
Errata to: Type-2 Fuzzy Graphical Models for Pattern Recognition....Pages E1-E1

✦ Subjects

Computational Intelligence; Artificial Intelligence (incl. Robotics); Pattern Recognition; Signal, Image and Speech Processing