Adaptive filtering and change detection
Wiley, 2001
Adaptive filtering is a classical branch of digital signal
processing (DSP) and its industrial interest grows continuously
with the increase in computer performance allowing even rather complex
algorithms to be run in real-time.
On the other hand, change detection is another kind of adaptive
filtering for non-stationary signals which has up to now been seen as a
theoretical subject with few applications in practice.
Change detection is also the basic tool in fault detection and
diagnosis.
The book bridges a gap in literature with a unified treatment of these
areas, stressing that change detection is a natural extension of adaptive filters,
and adaptive filters are basic building blocks in all change detectors.
The book is rather broad in that it covers many disciplines both
regarding mathematical tools (algebra, calculus, statistics) and
applications areas (airborne, automotive, communication systems and
also standard signal processing and automatic control applications),
and its strong points include:
-
Thoroughly worked out real world examples, which illustrate quite
involved results.
-
A unifying framework for the theory of change detection based on a
filtering approach.
-
A complete treatment of adaptive filtering
The book is suitable for:
-
master students specializing in DSP,
-
graduate students in electrical engineering,
-
applied engineers and researchers in the field of model based DSP.
Examples and algorithms are illustrated in Matlab, and
the 130 examples and case studies can be reproduced and investigated
in an accompanying Matlab demo toolbox.
Contact the authors:
Fredrik Gustafsson