This second edition of Adaptive Filters: Theory and Applications has been updated throughout to reflect the latest developments in this field; notably an increased coverage given to the practical applications of the theory to illustrate the much broader range of adaptive filters applications developed in recent years. The book offers an easy to understand approach to the theory and application of adaptive filters by clearly illustrating how the theory explained in the early chapters of the book is modified for the various applications discussed in detail in later chapters. This integrated approach makes the book a valuable resource for graduate students; and the inclusion of more advanced applications including antenna arrays and wireless communications makes it a suitable technical reference for engineers, practitioners and researchers.
Key Features
- Offers a thorough treatment of the theory of adaptive signal processing; incorporating new material on transform domain, frequency domain, subband adaptive filters, acoustic echo cancellation and active noise control.
- Provides an in-depth study of applications which now includes extensive coverage of OFDM, MIMO and smart antennas.
- Contains exercises and computer simulation problems at the end of each chapter.
- Includes a new companion website hosting MATLAB simulation programs which complement the theoretical analyses, enabling the reader to gain an in-depth understanding of the behaviours and properties of the various adaptive algorithms.
Contents
Chapter 1 Introduction
- 1.1 Linear Filters
- 1.2 Adaptive Filters
- 1.3 Adaptive Filter Structures
- 1.4 Adaptation Approaches
- 1.5 Real and Complex Forms of Adaptive Filters
- 1.6 Applications
Chapter 2 Discrete-Time Signals and Systems
- 2.1 Sequences and z-Transform
- 2.2 Parseval’s Relation
- 2.3 System Function
- 2.4 Stochastic Processes
Chapter 3 Wiener Filters
- 3.1 Mean-Squared Error Criterion
- 3.2 Wiener Filter - Transversal, Real-valued Case
- 3.3 Principle of Orthogonality
- 3.4 Normalized Performance Function
- 3.5 Extension to Complex-Valued Case
- 3.6 UnconstrainedWiener Filters
- 3.7 Summary and Discussion
Chapter 4 Eigenanalysis and Performance Surface
- 4.1 Eigenvalues and Eigenvectors
- 4.2 Properties of Eigenvalues and Eigenvectors
- 4.3 Performance Surface
Chapter 5 Search Methods
- 5.1 Method of Steepest-Descent
- 5.2 Learning Curve
- 5.3 Effect of Eigenvalue-Spread
- 5.4 Newton’s Method
- 5.5 An Alternative Interpretation of Newton’s Algorithm
Chapter 6 LMS Algorithm
- 6.1 Derivation of LMS Algorithm
- 6.2 Average Tap-Weight Behavior of the LMS Algorithm
- 6.3 MSE Behavior of the LMS Algorithm 1
- 6.4 Computer Simulations
- 6.5 Simplified LMS Algorithms
- 6.6 Normalized LMS Algorithm
- 6.7 Affine Projection LMS Algorithm
- 6.8 Variable Step-Size LMS Algorithm
- 6.9 LMS Algorithm for Complex-Valued Signals
- 6.10 Beamforming (Revisited)
- 6.11 Linearly Constrained LMS Algorithm
Chapter 7 Transform Domain Adaptive Filters
- 7.1 Overview of Transform Domain Adaptive Filters
- 7.2 Band-Partitioning Property of Orthogonal Transforms
- 7.3 Orthogonalization Property of Orthogonal Transforms
- 7.4 Transform Domain LMS Algorithm
- 7.5 Ideal LMS-Newton Algorithm and Its Relationship with TDLMS
- 7.6 Selection of the transform T
- 7.7 Transforms
- 7.8 Sliding Transforms
- 7.9 Summary and Discussion
Chapter 8 Block Implementation of Adaptive Filters
- 8.1 Block LMS Algorithm
- 8.2 Mathematical Background
- 8.3 The FBLMS Algorithm
- 8.4 The Partitioned FBLMS Algorithm
- 8.5 Computer Simulations
Chapter 9 Subband Adaptive Filters
- 9.1 DFT Filter Banks
- 9.2 Complementary Filter Banks
- 9.3 Subband Adaptive Filter Structures
- 9.4 Selection of Analysis and Synthesis Filters
- 9.5 Computational Complexity
- 9.6 Decimation Factor and Aliasing
- 9.7 Low-Delay Analysis and Synthesis Filter Banks
- 9.8 A Design Procedure for Subband Adaptive Filters
- 9.9 An Example
- 9.10 Comparison with FBLMS Algorithm
Chapter 10 IIR Adaptive Filters
- 10.1 Output Error Method
- 10.2 Equation Error Method
- 10.3 Case Study I: IIR Adaptive Line Enhancement
- 10.4 Case Study II: Equalizer Design for Magnetic Recording Channels
- 10.5 Concluding Remarks
Chapter 11 Lattice Filters
- 11.1 Forward Linear Prediction
- 11.2 Backward Linear Prediction
- 11.3 Relationship Between Forward and Backward Predictors
- 11.4 Prediction-Error Filters
- 11.5 Properties of Prediction Errors
- 11.6 Derivation of Lattice Structure
- 11.7 Lattice as an Orthogonalization Transform
- 11.8 Lattice Joint Process Estimator
- 11.9 System Functions
- 11.10 Conversions
- 11.11 All-Pole Lattice Structure
- 11.12 Pole-Zero Lattice Structure
- 11.13 Adaptive Lattice Filter
- 11.14 Autoregressive Modeling of Random Processes
- 11.15 Adaptive Algorithms Based on Autoregressive Modeling
Chapter 12 Method of Least-Squares
- 12.1 Formulation of Least-Squares Estimation for a Linear Combiner
- 12.2 Principle of Orthogonality
- 12.3 Projection Operator
- 12.4 Standard Recursive Least-Squares Algorithm
- 12.5 Convergence Behavior of the RLS Algorithm
Chapter 13 Fast RLS Algorithms
- 13.1 Least-Squares Forward Prediction
- 13.2 Least-Squares Backward Prediction
- 13.3 Least-Squares Lattice
- 13.4 RLSL Algorithm
- 13.5 FTRLS Algorithm
Chapter 14 Tracking
- 14.1 Formulation of the Tracking Problem
- 14.2 Generalized Formulation of LMS Algorithm
- 14.3 MSE Analysis of the Generalized LMS Algorithm
- 14.4 Optimum Step-Size Parameters
- 14.5 Comparisons of Conventional Algorithms
- 14.6 Comparisons Based on Optimum Step-Size Parameters
- 14.7 VSLMS: An algorithm with Optimum Tracking Behavior
- 14.8 RLS Algorithm with Variable Forgetting Factor
- 14.9 Summary
Chapter 15 Echo Cancellation
- 15.1 The Problem Statement
- 15.2 Structures and Adaptive Algorithms
- 15.3 Double-Talk Detection
- 15.4 Howling Suppression
- 15.5 Stereophonic Acoustic Echo Cancellation
Chapter 16 Active Noise Control
- 16.1 Broadband Feedforward Single-Channel ANC
- 16.2 Narrowband Feedforward Single-Channel ANC
- 16.3 Feedback Single-Channel ANC
- 16.4 Multi-Channel ANC Systems
Chapter 17 Synchronization and Equalization in Data Transmission Systems
- 17.1 Continuous Time Channel Model
- 17.2 Discrete Time Channel Model and Equalizer Structures
- 17.3 Timing Recovery
- 17.4 Equalizers Design and Performance Analysis
- 17.5 Adaptation Algorithms
- 17.6 Cyclic Equalization
- 17.7 Joint Timing Recovery, Carrier Recovery and Channel Equalization
- 17.8 Maximum Likelihood Detection
- 17.9 Soft Equalization
- 17.10 Single-Input Multiple-Output Equalization
- 17.11 Frequency Domain Equalization
- 17.12 Blind Equalization
18 Sensor Array Processing
- 18.1 Narrowband Sensor Arrays
- 18.2 Broadband Sensor Arrays
- 18.3 Robust Beamforming
19 Code Division Multiple Access Systems
- 19.1 CDMA Signal Model
- 19.2 Linear Detectors
- 19.3 Adaptation Methods
20 OFDM and MIMO Communications
- 20.1 OFDM Communication Systems
- 20.2 MIMO Communication Systems
- 20.3 MIMO-OFDM
Book Details
- Hardcover: 800 pages
- Publisher: Wiley; 2 edition (June, 2013)
- Language: English
- ISBN-10: 1119979544
- ISBN-13: 978-1119979548
- Product Dimensions: 6.8 x 1.6 x 9.6 inches
- List Price: $149.95