Table of Contents

Chapter 1 Introduction
1.1 Discrete-Time Stochastic Processes
1.2 Signal Modeling
1.3 Spectrum Estimation
1.4 Optimal Filters
1.5 Adaptive Filters
1.6 Organization of This Book
Chapter 2 Discrete Time Stochastic Processes
2.1 Introduction
2.2 Definitions of Random Processes
2.3 Time-Domain Statistical Characteristics
2.4 Frequency-Domain Statistical Characteristics
2.5 Filtering Random Processes
2.6 Special Types of Random Processes
2.7 Summary
Exercises
References
Chapter 3 Signal Modeling
3.1 Introduction
3.2 All-Pole Models
3.3 All-Zero Models
3.4 Pole-Zero Models
3.5 Summary
Exercises
References
Chapter 4 Spectrum Estimation
4.1 Introduction
4.2 Nonparametric Methods
4.3 Parametric Methods
4.4 Other Methods
4.5 Summary
Exercises
References
Chapter 5 Optimum Filters
5.1 Introduction
5.2 The FIR Wiener Filter
5.3 The IIR Wiener Filter
5.4 Least-Squares Filter
5.5 Discrete Kalman Filter
5.6 Summary
Exercises
References
Chapter 6 Adaptive Filters
6.1 Introduction
6.2 LMS Adaptive Filter
6.3 Affine Projection Adaptive Filter
6.4 RLS Adaptive Filter
6.5 Summary
Exercises
References