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Neural Networks and the Classification of Active Galactic Nucleus Spectra
Published online by Cambridge University Press: 25 April 2016
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.
- Type
- Extragalactic
- Information
- Publications of the Astronomical Society of Australia , Volume 13 , Issue 3 , June 1996 , pp. 207 - 211
- Copyright
- Copyright © Astronomical Society of Australia 1996
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