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Neural networks and the classification of active galactic nucleus spectra

Rawson, D. M.; Bailey, J.; Francis, Paul


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.

CollectionsANU Research Publications
Date published: 1996
Type: Journal article
Source: Publications of the Astronomical Society of Australia
Access Rights: Open Access


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