Bootstrap based signal denoising
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Authors
Kan, Hasan Ertam
Subjects
Denoising
Bootstrap
Kurtosis
Bootstrap
Kurtosis
Advisors
Fargues, Monique P.
Hippenstiel, Ralph D.
Date of Issue
2002-09
Date
September 2002
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
"This work accomplishes signal denoising using the Bootstrap method when the additive noise is Gaussian. The noisy signal is separated into frequency bands using the Fourier or Wavelet transform. Each frequency band is tested for Gaussianity by evaluating the kurtosis. The Bootstrap method is used to increase the reliability of the kurtosis estimate. Noise effects are minimized using a hard or soft thresholding scheme on the frequency bands that were estimated to be Gaussian. The recovered signal is obtained by applying the appropriate inverse transform to the modified frequency bands. The denoising scheme is tested using three test signals. Results show that FFT-based denoising schemes perform better than WT-based denoising schemes on the stationary sinusoidal signals, whereas WT-based schemes outperform FFT-based schemes on chirp type signals. Results also show that hard thresholding never outperforms soft thresholding, at best its performance is similar to soft thresholding."--p.i.
Type
Thesis
Description
Series/Report No
Department
Electrical and Computer Engineering
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
xvi, 91 p. : ill.
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
Rights
Coopyright is reserved by the copyright owner.