Pattern Recognition and Neural Networks

Ripley, Brian D.

ISBN 10: 0521717701 / ISBN 13: 9780521717700

Published by Cambridge University Press, 2008

About this Item

Ships from the UK. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects. Seller Inventory # 17325730-6

Bibliographic Details

Title: Pattern Recognition and Neural Networks

Publisher: Cambridge University Press

Publication Date: 2008

Binding: Soft cover

Condition: Very Good

Edition: 1st Edition.

About this title

Synopsis:

Ripley brings together two crucial ideas in pattern recognition: statistical methods and machine learning via neural networks. He brings unifying principles to the fore, and reviews the state of the subject. Ripley also includes many examples to illustrate real problems in pattern recognition and how to overcome them.

Review:

This book uses tools from statistical decision theory and computational learning theory to create a rigorous foundation for the theory of neural networks. On the theoretical side, Pattern Recognition and Neural Networks emphasizes probability and statistics. Almost all the results have proofs that are often original. On the application side, the emphasis is on pattern recognition. Most of the examples are from real world problems. In addition to the more common types of networks, the book has chapters on decision trees and belief networks from the machine-learning field. This book is intended for use in graduate courses that teach statistics and engineering. A strong background in statistics is needed to fully appreciate the theoretical developments and proofs. However, undergraduate-level linear algebra, calculus, and probability knowledge is sufficient to follow the book.