Wiener Filtering with Spectrum Estimation by Wavelet Transformation

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F01%3APU20798" target="_blank" >RIV/00216305:26220/01:PU20798 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Wiener Filtering with Spectrum Estimation by Wavelet Transformation

Popis výsledku v původním jazyce

Current methods used to improve the signal?to?noise ratio mainly employ the Wiener filtering, or methods derived from it, such as spectral subtraction. All these methods assume that it is possible to determine or at least to estimate noise spectral characteristics. As can be derived, the estimation by the periodogram is not exact, but it contains a disturbance. Averaging the power spectra offers better results but the properties are simultaneously downgraded by a non-stationary disturbance. That is whythe paper deals with the improvement of the power spectral density (PSD) estimation. To achieve this purpose we use the method of thresholding wavelet?transform coefficients, which we apply to each periodogram separately. Then the resultant estimation isused for the Wiener filter. The differences between the estimations obtained by the periodogram, by averaging and by this new method are shown in the paper. When we use wavelet transformation, a marked improvement in suppressing the dist

Název v anglickém jazyce

Wiener Filtering with Spectrum Estimation by Wavelet Transformation

Popis výsledku anglicky

Current methods used to improve the signal?to?noise ratio mainly employ the Wiener filtering, or methods derived from it, such as spectral subtraction. All these methods assume that it is possible to determine or at least to estimate noise spectral characteristics. As can be derived, the estimation by the periodogram is not exact, but it contains a disturbance. Averaging the power spectra offers better results but the properties are simultaneously downgraded by a non-stationary disturbance. That is whythe paper deals with the improvement of the power spectral density (PSD) estimation. To achieve this purpose we use the method of thresholding wavelet?transform coefficients, which we apply to each periodogram separately. Then the resultant estimation isused for the Wiener filter. The differences between the estimations obtained by the periodogram, by averaging and by this new method are shown in the paper. When we use wavelet transformation, a marked improvement in suppressing the dist

Druh

D - Stať ve sborníku

CEP obor

JA - Elektronika a optoelektronika, elektrotechnika

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F00%2F1084" target="_blank" >GA102/00/1084: RTD technologie hláskové separace zamaskované v hluku</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2001

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of International Conference on Trends in Communications

ISBN

0-7803-6490-2

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

471-474

Název nakladatele

FEI STU

Místo vydání

Bratislava, Slovensko

Místo konání akce

Bratislava

Datum konání akce

4. 7. 2001

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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