Applied Neural Networks for Signal Processing

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.

' … the book undoubtedly provides an interesting framework for new potential solutions and can therefore be recommended to a wide audience.' Zamp, 'This is a difficult but valuable book on the rapidly expanding use of neural networks to identify signals of many varieties.' David Bugg, Contemporary Physics, The appearance of the book Applied Neural Networks for Signal Processing by Fa-Long Luo and Rolf Unbehauen marks the end of a long wait for a textbook that deals comprehensively with this increasingly important subject. This book should prove invaluable to researchers as well as advanced graduate students in electrical engineering. The material is quite appropriate for a 3-4 credit hour graduate level course in electrical engineering, and I would unhesitatingly recommend this book as the main text for any such course. Sanjoy Das, Neurocomputing 1998, 'In this book, Luo and Unbehauen do an excellent job of demystifying most aspects of neural networks. The pleasant result is that the reader quickly gets a feeling for the nature of the proofs and an understanding of the performance of neural networks. A further plus for the book is that the notation of the book is clean and well explained, with the result that the formulas and proofs generally are easy to follow.' Collin C. Carbno, Society for Industrial and Applied Mathematics, '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