Please use this identifier to cite or link to this item: http://hdl.handle.net/2248/6390
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dc.contributor.authorGiridhar, S-
dc.contributor.authorGoswami, A-
dc.contributor.authorKunder, A-
dc.contributor.authorMuneer, S-
dc.contributor.authorSelvakumar, G-
dc.date.accessioned2013-09-25T10:03:56Z-
dc.date.available2013-09-25T10:03:56Z-
dc.date.issued2012-
dc.identifier.citationASI Conference Series, Vol. 6, pp. 137-142en
dc.identifier.isbn978-81-922926-4-9-
dc.identifier.urihttp://hdl.handle.net/2248/6390-
dc.descriptionOpen Accessen
dc.description.abstractAn update on recent methods for automated stellar parametrization is given. We present preliminary results of the ongoing program for rapid parametrization of field stars using medium resolution spectra obtained using Vainu Bappu Telescope at VBO, Kavalur, India. We have used Artificial Neural Network (ANN) for estimating temperature, gravity, metallicity and absolute magnitude of the field stars. The network for each parameter is trained independently using a large number of calibrating stars. The trained network is used for estimating atmospheric parameters of unexplored field stars.en
dc.language.isoenen
dc.publisherAstronomical Society of Indiaen
dc.relation.urihttp://adsabs.harvard.edu/abs/2012ASInC...6..137Gen
dc.rights© Astronomical Society of Indiaen
dc.subjectStellar abundancesen
dc.subjectANNen
dc.subjectAbsolute magnitudeen
dc.titleThe stellar parametrization using Artificial Neural Networken
dc.typeArticleen
Appears in Collections:IIAP Publications

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