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SYSEL, P. SMÉKAL, Z.
Originální název
Power Spectral Density Noise Estimation using Wavelet Transform in Spectral Domain
Typ
článek ve sborníku ve WoS nebo Scopus
Jazyk
angličtina
Originální abstrakt
The paper describes the design of a new method of power spectral density estimation using the wavelet transform in the spectral domain. To reduce periodogram variance the proposed method uses the procedure of thresholding the wavelet coefficients of a periodogram. The periodogram is decomposed into a chosen number of levels using the discrete wavelet transform with the appropriate mother wavelet. Then the thresholds used for the wavelet transform coefficients in dependence on the level are calculated. To threshold the wavelet transform coefficients soft thesholding is used. Then the smoothed estimate of power spectral density of noise is obtained using the inverse discrete wavelet transform. This reduces the variance of the estimate of power spectral density of noise.
Klíčová slova
power spectral density, estimation bias, estimation variance, spectral subtraction
Autoři
SYSEL, P.; SMÉKAL, Z.
Rok RIV
2007
Vydáno
21. 9. 2007
Místo
Praha
ISBN
978-80-86269-00-9
Kniha
Proceedings of 17th Czech-German Workshop Speech Processing
Strany od
98
Strany do
105
Strany počet
8
BibTex
@inproceedings{BUT25587, author="Petr {Sysel} and Zdeněk {Smékal}", title="Power Spectral Density Noise Estimation using Wavelet Transform in Spectral Domain", booktitle="Proceedings of 17th Czech-German Workshop Speech Processing", year="2007", pages="98--105", address="Praha", isbn="978-80-86269-00-9" }