Introduction to Statistical Pattern Recognition
This completely revised second edition presents an introduction to statistical pattern recognition. Pattern recognition in general covers a wide range of problems: it is applied to engineering problems, such as character readers and wave form analysis as well as to brain modeling in biology and psychology. Statistical decision and estimation, which are the main subjects of this book, are regarded as fundamental to the study of pattern recognition. This book is appropriate as a text for introductory courses in pattern recognition and as a reference book for workers in the field. Each chapter contains computer projects as well as exercises.
What people are saying - Write a review
No nonsense! Statistical pattern recognition in its purest form. I love this book.
I think this book is very useful for people with some statistical background knowledge (maybe not too much), and it contains a lot of basic ideas of many engineering problems, though some of them might need an upgrade for nowadays.
Chapter 4 PARAMETRIC CLASSIFIERS
Chapter 5 PARAMETER ESTIMATION
Chapter 6 NONPARAMETRIC DENSITY ESTIMATION
Chapter 7 NONPARAMETRIC CLASSIFICATION AND ERROR ESTIMATION
Chapter 8 SUCCESSIVE PARAMETER ESTIMATION
Chapter 9 FEATURE EXTRACTION AND LINEAR MAPPING FOR SIGNAL REPRESENTATION
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