Preface The use of patten recognition and classification is fundamental to many of the automated electronic systems in use today. Its applications range from military efense to medical diagnosis, from biometrics to machine learning, from bioinfor- matics to home entertainment, and more. However, despite the existence of a number of notable books in the field, the subject remains very challenging, espe We have found that the current textbooks are not completely satisfactory for our students, who are primarily computer science students but also include students from mathematics and physics backgrounds and those from industry. Their mathe matical and computer backgrounds are considerably varied, but they all want to understand and absorb the core concepts with a minimal time investment to the point where they can use and adapt them to problems in their own fields. Texts with extensive mathematical or statistical prerequisites were daunting and unappealing to them. Our students complained of"not seeing the wood for the trees, which is rather ironic for textbooks in pattern recognition. It is crucial for newcomers to the field to be introduced to the key concepts at a basic level in an ordered, logical fashion, so that they appreciate the"big picture"; they can then handle progres sively more detail, building on prior knowledge, without being overwhelmed. Too often our students have dipped into various textbooks to sample different approaches but have ended up confused by the different terminologies in use We have noticed that the majority of our students are very comfortable with and respond well to visual learning, building on their often limited entry knowledge, but focusing on key concepts illustrated by practical examples and exercises. We believe that a more visual presentation and the inclusion of worked examples promote a greater understanding and insight and appeal to a wider audience This book began as notes and lecture slides for a senior undergraduate course in Pattern Recognition at California State University Channel Islands(CSUCI). Over time it grew and approached its current form, which has been class tested over several years at CSUCI. It is suitable for a wide range of students at the advanced undergraduate or graduate level. It assumes only a modestPreface The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. Its applications range from military defense to medical diagnosis, from biometrics to machine learning, from bioinfor￾matics to home entertainment, and more. However, despite the existence of a number of notable books in the field, the subject remains very challenging, espe￾cially for the beginner. We have found that the current textbooks are not completely satisfactory for our students, who are primarily computer science students but also include students from mathematics and physics backgrounds and those from industry. Their mathe￾matical and computer backgrounds are considerably varied, but they all want to understand and absorb the core concepts with a minimal time investment to the point where they can use and adapt them to problems in their own fields. Texts with extensive mathematical or statistical prerequisites were daunting and unappealing to them. Our students complained of “not seeing the wood for the trees,” which is rather ironic for textbooks in pattern recognition. It is crucial for newcomers to the field to be introduced to the key concepts at a basic level in an ordered, logical fashion, so that they appreciate the “big picture”; they can then handle progres￾sively more detail, building on prior knowledge, without being overwhelmed. Too often our students have dipped into various textbooks to sample different approaches but have ended up confused by the different terminologies in use. We have noticed that the majority of our students are very comfortable with and respond well to visual learning, building on their often limited entry knowledge, but focusing on key concepts illustrated by practical examples and exercises. We believe that a more visual presentation and the inclusion of worked examples promote a greater understanding and insight and appeal to a wider audience. This book began as notes and lecture slides for a senior undergraduate course and a graduate course in Pattern Recognition at California State University Channel Islands (CSUCI). Over time it grew and approached its current form, which has been class tested over several years at CSUCI. It is suitable for a wide range of students at the advanced undergraduate or graduate level. It assumes only a modest v