Pattern Recognition Using Neural Networks

Carl G. Looney

ISBN 10: 0195079205 / ISBN 13: 9780195079203

Published by Oxford University Press Inc Feb 1997, 1997

About this Item

Neuware - Pattern Recognition Using Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks. The approach is algorithmic for easy implementation on a computer, which makes this a refreshing what-why-and-how text that contrasts with the theoretical approach and pie-in-the-sky hyperbole of many books on neural networks. It covers the standard decision-theoretic pattern recognition of clustering via minimumdistance, graphical and structural methods, and Bayesian discrimination. Looney has written a graduate level textbook combining the fields of pattern recognition and neural networks. It contains some theory of why the most useful networks work, the pitfalls, the algorithms to implement them, and their applications. This text is suitable for an advanced undergraduate or graduate level course in pattern recognition or neural networks for students in computer science or electrical and computer engineering. It is also useful as a reference and a resource for practitioners and researchers.

Seller Inventory # 9780195079203

Bibliographic Details

• Title: Pattern Recognition Using Neural Networks
• Publisher: Oxford University Press Inc Feb 1997
• Publication Date: 1997
• Language: English
• ISBN 10: 0195079205
• ISBN 13: 9780195079203
• Binding: Buch
• Condition: Neu

About this title

Synopsis

Pattern Regcognition with Neural Networks covers traditional linear pattern recognition and its nonlinear extension via neural networks from an algorithmic approach. The author has written a real-world practical "why-and-how" text that provides a refreshing contrast to competing texts' thoeretical appraoch and "pie-in-the-sky" claims. The text explores mulitple layered preceptrons and describes network types such as functional link, radial basis function, learning vector quantanization and self-organizing. The author also discusses recent clustering methods. This text is suitable for an advanced undergraduate course in pattern recognition or neural networks, and is also useful as a reference and a resource.

About the Author

Carl Grant Looney is Professor and Director of the Graduate Program in the Computer Science Department at the University of Nevada in Reno.