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Title:
Neural networks and the classification of active galactic nucleus spectra
Authors:
Rawson, D. M.; Bailey, J.; Francis, P. J.
Publication:
Publications Astronomical Society of Australia, vol. 13, no. 3, p. 207-211 (PASA Homepage)
Publication Date:
11/1996
Origin:
PASA
Keywords:
GALAXIES, QUASARS, SEYFERTS
Bibliographic Code:
1996PASA...13..207R

Abstract

The use of artificial neural networks (ANNs) as a classifier of digital spectra is investigated. Using both simulated and real data, it is shown that neural networks can be trained to discriminate between the spectra of different classes of active galactic nucleus (AGN) with realistic sample sizes and signal-to-noise ratios. By working in the Fourier domain, neural nets can classify objects without knowledge of their redshifts.

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