Applied Neural Networks for Signal Processing

Features

• Cover Type: Paperback with 382 pages
• Published by: Cambridge University Press January 1999
• Written in: English
• ISBN 10 Number: 0521644003
• ISBN 13 Number: 978-0521644006
• Book Dimensions: 10 x 7 x 0.8 inches
• Weighs: 1.5 pounds

Product Review
"an interesting reference for scientists and engineers working in signal processing and also a good textbook for graduate students of electronics engineering can contribute to improving the understanding of the realistic potentialities of neural networks for signal processing and to making their use more effective." Neural Networks

"Luo and Unbehauenshould be congratulated on the judicious selection of topics and skillful mix of mathematical rigor and neural nets implementationsOverall the book offers a balanced and in-depth treatment of neural nets applications in signal processing and will benefit both students and researchers in the field." Signal Processing

"Indeed, the book is very well assembled, with highly coherent presentation, mathematically and otherwise, and represents a useful volume for student and practitionerthis volume is worthy of serious consideration for its useful marriage of neural networks with mostly 1D signal processing topics, and for its careful integration of the materialI wholeheartedly recommend it." Contemporary Physics

"In this book, Luo and Unbehauen do an great job of demystifying most aspects of neural networksLuo and Unbehauen are also to be commended on the breadth of different neural networks topics covered by the bookthe authors have done a remarkable job of condensing and organizing the materialIn short, if you need to understand how neural networks can help in signal processing problems, this book is a must." SIAM Review

Product Description
The use of neural networks in signal processing is becoming increasingly widespread, with applications in many areas. Applied Neural Networks for Signal Processing is the first book to provide a comprehensive introduction to this broad field. It begins by covering the basic principles and models of neural networks in signal processing. The authors then discuss a number of powerful algorithms and architectures for a range of important problems, and describe practical implementation procedures. A key feature of the book is that many carefully designed simulation examples are included to help guide the reader in the development of systems for new applications. The book will be an invaluable reference for scientists and engineers working in communications, control or any other field related to signal processing. It can also be used as a textbook for graduate courses in electrical engineering and computer science.