Applied Neural Networks for Signal Processing

by Fa-Long Luo , Rolf Unbehauen

• ISBN13: 9780521644006
• ISBN10: 0521644003
• Format: Paperback
• Copyright: 1999-01-13
• Publisher: Cambridge University Press

Summary

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.

Table of Contents

Preface	ix
Fundamental Models of Neural Networks for Signal Processing	1	(31)
The discrete-Time Hopfield Neural Network	1	(4)
The Continuous-Time Hopfield Neural Network	5	(6)
Cellular Neural Networks	11	(5)
Multilayer Perceptron Networks	16	(4)
Self-Organizing Systems	20	(2)
Radial Basis Function Networks	22	(4)
High-Order Neural Networks	26	(6)
Bibliography	29	(3)
Neural Networks for Filtering	32	(42)
Neural Network for the Least-Squares Algorithm	33	(12)
Neural Networks for the Recursion Least-Squares Algorithm	45	(4)
Neural Networks for the Constrained Least-Squares Algorithm	49	(2)
Neural Networks for the Total-Least-Squares Algorithm	51	(7)
Neural Networks for a Class of Nonlinear Filters	58	(3)
Neural Networks for General Nonlinear Filters	61	(4)
Fundamentals	61	(2)
An Application Example: Signal Prediction	63	(2)
Neural Networks for Generalized Stack Filters	65	(9)
Bibliography	71	(3)
Neural Networks for Spectral Estimation	74	(47)
Maximum Entropy Spectral Estimation by Neural Networks	74	(6)
Harmonic Retrieval by Neural Networks	80	(14)
Neural Networks for Multichannel Spectral Estimation	94	(14)
Neural Networks for Two-Dimensional Spectral Estimation	108	(4)
Neural Networks for Higher-Order Spectral Estimation	112	(9)
Bibliography	117	(4)
Neural Networks for Signal Detection	121	(31)
A Likelihood-Ratio Neural Network Detector	122	(4)
Fundamentals of the Likelihood-Ratio Detector	122	(2)
Structure of the Likelihood-Ratio Neural Network Detector	124	(2)
Neural Networks for Signal Detection in Non-Gaussian Noise	126	(4)
Neural Networks for Pulse Signal Detection	130	(4)
Neural Networks for Weak Signal Detection in High-Noise Environments	134	(4)
Neural Networks for Moving-Target Detection	138	(14)
Bibliography	150	(2)
Neural Networks for Signal Reconstruction	152	(36)
Maximum Entropy Signal Reconstruction by Neural Networks	153	(9)
Reconstruction of Binary Signals Using MLP Networks	162	(6)
Reconstruction of Binary Signals Using RBF Networks	168	(9)
Reconstruction of Binary Signals Using High-Order Neural Networks	177	(4)
Blind Equalization Using Neural Networks	181	(7)
Bibliography	185	(3)
Neural Networks for Adaptive Extraction of Principal and Minor Components	188	(52)
Adaptive Extraction of the First Principal Component	188	(13)
Adaptive Extraction of the Principal Subspace	201	(4)
Adaptive Extraction of the Principal Components	205	(11)
Adaptive Extraction of the Minor Components	216	(13)
Adaptive Extraction of the First Minor Component	217	(6)
Adaptive Extraction of the Multiple Minor Components	223	(6)
Robust and Nonlinear PCA Algorithms and Networks	229	(4)
Unsupervised Learning Algorithms of Higher-Order Statistics	233	(7)
Bibliography	236	(4)
Neural Networks for Array Signal Processing	240	(54)
Real-Time Implementation of Three DOA Estimation Methods Using Neural Networks	241	(11)
The ML and Alternating Projection ML Methods	241	(3)
The Propagator Method	244	(2)
Real-Time Computation of the DOA Algorithms Using Neural Networks	246	(6)
Neural Networks for the MUSIC Bearing Estimation Algorithm	252	(19)
Computation of the Noise Subspace of the Repeated Smallest Eigenvalues	254	(8)
Computation of the Noise Subspace in the General Case	262	(9)
Neural Networks for the ML Bearing Estimation	271	(9)
Hypothesis-Based Bearing Estimation Using Neural Networks	280	(7)
Beamforming Using Neural Networks	287	(7)
Bibliography	292	(2)
Neural Networks for System Identification	294	(41)
Fundamentals of System Identification	294	(4)
System Identification Using MLP Networks	298	(13)
System Identification Using RBF Networks	311	(6)
Recurrent Neural Networks for System Identification	317	(6)
Neural Networks for Real-Time System Identification	323	(6)
Neural Networks for Real-Time Identification of SISO Systems	323	(4)
Neural Networks for Real-Time Identification of MIMO Systems	327	(2)
Blind System Identification and Neural Networks	329	(6)
Bibliography	332	(3)
Neural Networks for Signal Compression	335	(30)
Neural Networks for Linear Predictive Coding	336	(6)
MLP Networks for Nonlinear Predictive Coding	342	(4)
High-Order Neural Networks for Nonlinear Predictive Coding	346	(4)
Neural Networks for the Karhunen-Loeve Transform Coding	350	(5)
Neural Networks for Wavelet Transform Coding	355	(3)
Neural Networks for Vector Quantization	358	(7)
Bibliography	362	(3)
Index	365