Comparative performance of artificial neural networks for UV spectral classification

dc.contributor.authorMukherjee, Soma
dc.contributor.authorBhattacharya, Ujwal
dc.contributor.authorParui, S.K
dc.contributor.authorGupta, Ranjan
dc.contributor.authorGulati, R.K
dc.date.accessioned2015-02-07T07:07:31Z
dc.date.available2015-02-07T07:07:31Z
dc.date.issued2015-02-07
dc.description.abstractIn this paper we present an application of an artificial neural network model based on a multi-layered back propagation algorithm for spectral classification of UV data from the International Ultraviolet Explorer (IUE) low dispersion spectra reference atlas. The model used is similar to that of von Rippel et al. (1994), and is found to reduce the classification error as compared to .the recently reported results on the same data set (Gulati et al. 1994b ). The improved version of the network is much simpler in structure and the training time is reduced by a factor of almost 20. Such networks will prove very useful in efficient classification of large databasesen_US
dc.identifier.urihttp://hdl.handle.net/11007/2837
dc.language.isoenen_US
dc.relation.ispartofseriesIUCAA Preprint; 45/1995;
dc.subjectArtificial neural networken_US
dc.subjectSpectral classificationen_US
dc.titleComparative performance of artificial neural networks for UV spectral classificationen_US
dc.typeArticleen_US

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