Publication detail

Feature Extraction Using Wavelet Power Spectrum for Stellar Spectra Clustering

ŠKODA, P. VRÁBELOVÁ, P. ZENDULKA, J.

Original Title

Feature Extraction Using Wavelet Power Spectrum for Stellar Spectra Clustering

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper analyses the capabilities of using wavelet power spectrum for clustering of Be-type stars spectra. We propose a method using discrete wavelet transform for feature extraction and the wavelet power spectrum as a feature vector. We also propose a modification of this method and compare them. We analyse the methods in the clustering of artificial stellar spectra and compare them with a traditional method of wavelet-based feature extraction -- keeping $k$ largest coefficients. The results show that the correctness of clustering of our method is significantly better than in the case of a traditional method. We also compare the effect of using different type of wavelet and level of decomposition.

Authors

ŠKODA, P.; VRÁBELOVÁ, P.; ZENDULKA, J.

Released

28. 5. 2012

Location

Praha

ISBN

978-80-7378-220-7

Book

Proceedings of the 11th annual conference Znalosti 2012

Pages from

31

Pages to

40

Pages count

10

URL

https://www.fit.vut.cz/research/publication/10061/

BibTex

@inproceedings{BUT106560,
  author="Petr {Škoda} and Pavla {Vrábelová} and Jaroslav {Zendulka}",
  title="Feature Extraction Using Wavelet Power Spectrum for Stellar Spectra Clustering",
  booktitle="Proceedings of the 11th annual conference Znalosti 2012",
  year="2012",
  pages="31--40",
  address="Praha",
  isbn="978-80-7378-220-7",
  url="https://www.fit.vut.cz/research/publication/10061/"
}