Denoising signals is an important task of digital signal processing. Many linear
and non-linear methods for signal denoising have been developed. Wavelet based
denoising is the most famous nonlinear denoising method lately. In the linear case,
Kalman filter is famous for its easy implementation and real-time nature. Wavelet-
Kalman filter developed lately is an important improvement over Kalman filter, in
which the Kalman filter operates in the wavelet domain, filtering the wavelet coeffi-
cients, and resulting in the filtered wavelet transform of the signal in real-time. The
real-time filtering and multiresolution representation is a powerful feature for many
real world applications.
This study explains in detail the derivation and implementation of Real-Time
Wavelet-Kalman Filter method to remove noise from signals in real-time. The filter
is enhanced to use different wavelet types than the Haar wavelet, and also it is
improved to operate on higer block sizes than two. Wavelet shrinkage is integrated
to the filter and it is shown that by utilizing this integration more noise suppression
is obtainable. A user friendly application is developed to import, filter and export
signals in Java programming language. And finally, the applicability of the proposed
method to suppress noise from seismic waves coming from eartquakes and to enhance
spontaneous potentials measured from groundwater wells is also shown.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12608336/index.pdf |
| Date | 01 April 2007 |
| Creators | Durmaz, Murat |
| Contributors | Karslioglu, Mahmut Onur |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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