Automated spectral classification using template matching

Details Automated spectral classification using template matching Automated spectral classification using template matching

Mar 2009

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009raa.....9..341d&link_type=abstract

Research in Astronomy and Astrophysics, Volume 9, Issue 3, pp. 341-348 (2009).

Astronomy and Astrophysics

Astrophysics

1

Scientific paper

An automated spectral classification technique for large sky surveys is proposed. We firstly perform spectral line matching to determine redshift candidates for an observed spectrum, and then estimate the spectral class by measuring the similarity between the observed spectrum and the shifted templates for each redshift candidate. As a byproduct of this approach, the spectral redshift can also be obtained with high accuracy. Compared with some approaches based on computerized learning methods in the literature, the proposed approach needs no training, which is time-consuming and sensitive to selection of the training set. Both simulated data and observed spectra are used to test the approach; the results show that the proposed method is efficient, and it can achieve a correct classification rate as high as 92.9%, 97.9% and 98.8% for stars, galaxies and quasars, respectively.

Affiliated with

Also associated with

No associations

Rating

Automated spectral classification using template matching does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Automated spectral classification using template matching, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Automated spectral classification using template matching will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-1731768