Ebook: Adaptive Signal Processing: Theory and Applications
Author: S. Thomas Alexander
- Genre: Computers // Algorithms and Data Structures
- Tags: Communications Engineering Networks, Coding and Information Theory, Special Purpose and Application-Based Systems
- Series: Texts and Monographs in Computer Science
- Year: 1986
- Publisher: Springer
- Language: English
- pdf
The creation of the text really began in 1976 with the author being involved with a group of researchers at Stanford University and the Naval Ocean Systems Center, San Diego. At that time, adaptive techniques were more laboratory (and mental) curiosities than the accepted and pervasive categories of signal processing that they have become. Over the lasl 10 years, adaptive filters have become standard components in telephony, data communications, and signal detection and tracking systems. Their use and consumer acceptance will undoubtedly only increase in the future. The mathematical principles underlying adaptive signal processing were initially fascinating and were my first experience in seeing applied mathematics work for a paycheck. Since that time, the application of even more advanced mathematical techniques have kept the area of adaptive signal processing as exciting as those initial days. The text seeks to be a bridge between the open literature in the professional journals, which is usually quite concentrated, concise, and advanced, and the graduate classroom and research environment where underlying principles are often more important.
Content:
Front Matter....Pages i-ix
Introduction....Pages 1-7
The Mean Square Error (MSE) Performance Criteria....Pages 8-33
Linear Prediction and the Lattice Structure....Pages 34-45
The Method of Steepest Descent....Pages 46-67
The Least Mean Squares (LMS) Algorithm....Pages 68-86
Applications of the LMS Algorithm....Pages 87-98
Gradient Adaptive Lattice Methods....Pages 99-110
Chapter 8 Recursive Least Squares Signal Processing....Pages 111-122
Vector Spaces for RLS Filters....Pages 123-141
The Least Squares Lattice Algorithm....Pages 142-153
Fast Transversal Filters....Pages 154-176
Back Matter....Pages 177-179
Content:
Front Matter....Pages i-ix
Introduction....Pages 1-7
The Mean Square Error (MSE) Performance Criteria....Pages 8-33
Linear Prediction and the Lattice Structure....Pages 34-45
The Method of Steepest Descent....Pages 46-67
The Least Mean Squares (LMS) Algorithm....Pages 68-86
Applications of the LMS Algorithm....Pages 87-98
Gradient Adaptive Lattice Methods....Pages 99-110
Chapter 8 Recursive Least Squares Signal Processing....Pages 111-122
Vector Spaces for RLS Filters....Pages 123-141
The Least Squares Lattice Algorithm....Pages 142-153
Fast Transversal Filters....Pages 154-176
Back Matter....Pages 177-179
....