Applied Neural Networks for Signal Processing

A comprehensive introduction to the use of neural networks in signal processing.

Fa-Long Luo (Author), Rolf Unbehauen (Author)

9780521644006, Cambridge University Press

Paperback, published 13 January 1999

382 pages, 114 b/w illus. 13 tables
25.4 x 17.8 x 2 cm, 0.66 kg

'In short, if you need to understand how neural networks can help in signal processing problems, this book is a must.' Collin C. Carbno, Society for Industrial and Applied Mathematics

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.

1. Fundamental models of neural networks for signal processing
2. Neural networks for filtering
3. Neural networks for spectral estimation
4. Neural networks for signal detection
5. Neural networks for signal reconstruction
6. Neural networks for adaptive extraction of principal and minor components
7. Neural networks for array signal processing
8. Neural networks for system identification
9. Neural networks for signal compression.

Subject Areas: Neural networks & fuzzy systems [UYQN]