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Applied neural networks for signal processing / Fa-Long Luo and Rolf Unbehauen.
Author
Luo, Fa-Long
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Format
Book
Language
English
Published/Created
Cambridge, U.K. ; New York : Cambridge University Press, 1997.
Description
xi, 367 pages : illustrations ; 26 cm
Availability
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Call Number
Status
Location Service
Notes
ReCAP - Remote Storage
TK5102.9 .L85 1997
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Details
Subject(s)
Signal processing
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Neural networks (Computer science)
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Related name
Unbehauen, Rolf
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Summary note
The book 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 go on to describe practical implementation procedures. A key feature of the book is that many carefully designed 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.
Bibliographic references
Includes bibliographical references and index.
Contents
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.
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ISBN
0521563917
LCCN
96041384
OCLC
35285473
RCP
C - S
Statement on language in description
Princeton University Library aims to describe library materials in a manner that is respectful to the individuals and communities who create, use, and are represented in the collections we manage.
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Applied neural networks for signal processing / Fa-Long Luo, Rolf Unbehauen.
id
SCSB-9108920