Wavelet Based Feature Extraction for Clustering of Be Stars

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F13%3APU108491" target="_blank" >RIV/00216305:26230/13:PU108491 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985815:_____/13:00424303

Výsledek na webu

<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-00542-3_46" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-00542-3_46</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-00542-3_46" target="_blank" >10.1007/978-3-319-00542-3_46</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Wavelet Based Feature Extraction for Clustering of Be Stars

Popis výsledku v původním jazyce

The goal of our work is to create a feature extraction method for classification of Be stars. Be stars are characterized by prominent emission lines in their spectrum. We focus on the automated classification of Be stars based on typical shapes of their emission lines. We aim to design a reduced, specific set of features characterizing and discriminating the shapes of Be lines. In this paper, we present a feature extraction method based on the wavelet transform and its power spectrum. Both the discrete and continuous wavelet transform are used. Different feature vectors are created and compared on clustering of Be stars spectra from the archive of the Astronomical Institute of the Academy of Sciences of the Czech Republic. The clustering is performed using the k- means algorithm. The results of our method are promising and encouraging to more detailed analysis.

Název v anglickém jazyce

Wavelet Based Feature Extraction for Clustering of Be Stars

Popis výsledku anglicky

The goal of our work is to create a feature extraction method for classification of Be stars. Be stars are characterized by prominent emission lines in their spectrum. We focus on the automated classification of Be stars based on typical shapes of their emission lines. We aim to design a reduced, specific set of features characterizing and discriminating the shapes of Be lines. In this paper, we present a feature extraction method based on the wavelet transform and its power spectrum. Both the discrete and continuous wavelet transform are used. Different feature vectors are created and compared on clustering of Be stars spectra from the archive of the Astronomical Institute of the Academy of Sciences of the Czech Republic. The clustering is performed using the k- means algorithm. The results of our method are promising and encouraging to more detailed analysis.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název statě ve sborníku

Nostradamus 2013: Prediction, Modeling and Analysis of Complex Systems

ISBN

978-3-319-00541-6

ISSN

—

e-ISSN

—

Počet stran výsledku

9

Strana od-do

467-474

Název nakladatele

Springer US

Místo vydání

New York

Místo konání akce

VSB Technical University of Ostrava

Datum konání akce

3. 6. 2013

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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