Detail publikace

Power Spectral Density Noise Estimation using Wavelet Transform in Spectral Domain

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"
}