Adaptive filtering is a branch of digital signal processing which enables the selective enhancement of desired elements of a signal and the reduction of undesired elements. Change detection is another kind of adaptive filtering for non-stationary signals, and is the basic tool in fault detection and diagnosis. This text takes the unique approach that change detection is a natural extension of adaptive filtering, and the broad coverage encompasses both the mathematical tools needed for adaptive filtering and change detection and the applications of the technology. Real engineering applications covered include aircraft, automotive, communication systems, signal processing and automatic control problems. The unique integration of both theory and practical applications makes this book a valuable resource combining information otherwise only available in separate sources
- Comprehensive coverage includes many examples and case studies to illustrate the ideas and show what can be achieved
- Uniquely integrates applications to airborne, automotive and communications systems with the essential mathematical tools
- Accompanying Matlab toolbox available on the web illustrating the main ideas and enabling the reader to do simulations using all the figures and numerical examples featured
This text would prove to be an essential reference for postgraduates and researchers studying digital signal processing as well as practising digital signal processing engineers.
Author(s): Fredrik Gustafsson
Edition: 1
Publisher: Wiley
Year: 2000
Language: English
Pages: 510
Adaptive Filtering & Change Detection......Page 1
Copyright......Page 4
Contents......Page 5
Preface......Page 9
Part1 Introduction......Page 11
Ch1 Extended Summary......Page 13
Ch2 Applications......Page 41
Part2 Signal Estimation......Page 65
Ch3 On-Line Approaches......Page 67
Ch4 Off-Line Approaches......Page 99
Part3 Parameter Estimation......Page 121
Ch5 Adaptive Filtering......Page 123
Ch6 Change Detection based on Sliding Windows......Page 215
Ch7 Change Detection based on Filter Banks......Page 241
Part4 State Estimation......Page 271
Ch8 Kalman Filtering......Page 273
Ch9 Change Detection based on Likelihood Ratios......Page 353
Ch10 Change Detection based on Multiple Models......Page 387
Ch11 Change Detection based on Algebraical Consistency Tests......Page 413
Part5 Theory......Page 435
Ch12 Evaluation Theory......Page 437
Ch13 Linear Estimation......Page 461
AppA Signal Models & Notation......Page 481
AppB Fault Detection Terminology......Page 485
Bibliography......Page 487
Index......Page 503
