Classification of Spectra of Emission-line Stars Using Feature Extraction Based on Wavelet Transform

Kód výsledku v IS VaVaI

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Nalezeny alternativní kódy

RIV/00216305:26230/13:PU106402

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification of Spectra of Emission-line Stars Using Feature Extraction Based on Wavelet Transform

Popis výsledku v původním jazyce

Our goal is to automatically identify spectra of emission (Be) stars in large archives and classify their types based on a typical shape of the H? emission line. Due to the length of spectra, of the original data is very time-consuming. In order to lowercomputational requirements and enhance the separability of the classes, we have to find a reduced representation of spectral features, however conserving most of the original information content. As the Be stars show a number of different shapes of emission lines, it is not easy to construct simple criteria (like e.g. Gaussian fits) to distinguish the emission lines in an automatic manner. We proposed to perform the wavelet transform of the spectra, calculate statistical metrics from the wavelet coefficients, and use them as feature vectors for classification. In this paper, we compare different wavelet transforms, different wavelets, and different statistical metrics in an attempt to identify the best method.

Název v anglickém jazyce

Classification of Spectra of Emission-line Stars Using Feature Extraction Based on Wavelet Transform

Popis výsledku anglicky

Our goal is to automatically identify spectra of emission (Be) stars in large archives and classify their types based on a typical shape of the H? emission line. Due to the length of spectra, of the original data is very time-consuming. In order to lowercomputational requirements and enhance the separability of the classes, we have to find a reduced representation of spectral features, however conserving most of the original information content. As the Be stars show a number of different shapes of emission lines, it is not easy to construct simple criteria (like e.g. Gaussian fits) to distinguish the emission lines in an automatic manner. We proposed to perform the wavelet transform of the spectra, calculate statistical metrics from the wavelet coefficients, and use them as feature vectors for classification. In this paper, we compare different wavelet transforms, different wavelets, and different statistical metrics in an attempt to identify the best method.

Druh

D - Stať ve sborníku

CEP obor

BN - Astronomie a nebeská mechanika, astrofyzika

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Astronomical Data Analysis Software and Systems XXIII

ISBN

9781583818541

ISSN

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e-ISSN

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Počet stran výsledku

4

Strana od-do

177-180

Název nakladatele

Astronomical Society of the Pacific

Místo vydání

San Francisco

Místo konání akce

Waikoloa Beach Marriott

Datum konání akce

29. 9. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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