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http://hdl.handle.net/2248/6390
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DC Field | Value | Language |
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dc.contributor.author | Giridhar, S | - |
dc.contributor.author | Goswami, A | - |
dc.contributor.author | Kunder, A | - |
dc.contributor.author | Muneer, S | - |
dc.contributor.author | Selvakumar, G | - |
dc.date.accessioned | 2013-09-25T10:03:56Z | - |
dc.date.available | 2013-09-25T10:03:56Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | ASI Conference Series, Vol. 6, pp. 137-142 | en |
dc.identifier.isbn | 978-81-922926-4-9 | - |
dc.identifier.uri | http://hdl.handle.net/2248/6390 | - |
dc.description | Open Access | en |
dc.description.abstract | An 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.iso | en | en |
dc.publisher | Astronomical Society of India | en |
dc.relation.uri | http://adsabs.harvard.edu/abs/2012ASInC...6..137G | en |
dc.rights | © Astronomical Society of India | en |
dc.subject | Stellar abundances | en |
dc.subject | ANN | en |
dc.subject | Absolute magnitude | en |
dc.title | The stellar parametrization using Artificial Neural Network | en |
dc.type | Article | en |
Appears in Collections: | IIAP Publications |
Files in This Item:
File | Description | Size | Format | |
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The stellar parametrization using Artificial Neural Network.pdf | 512 kB | Adobe PDF | View/Open |
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