Browsing by Author "Gulati, R.K"

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    Comparative performance of artificial neural networks for UV spectral classification
    (2015-02-07) Mukherjee, Soma; Bhattacharya, Ujwal; Parui, S.K; Gupta, Ranjan; Gulati, R.K
    In 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 databases
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    A comparison of synthetic and observed spectra for G-K dwarfs using arti
    (Astron. Astrophys, 1967-01-18) Gulati, R.K; Gupta, Ranjan; Rao, N.K
    A library of synthetic spectra, based on Kurucz model atmospheres, has been used to compare the spectroscopic observations in thewavelength range 4850-5384 A by using statistical and supervised arti cial neural network methods. The effective temperatures assigned by these methods for G-K dwarfs are compared with those given in Gray and Corbally (1994) and found to be closely matching their calibration curve. This result provides a promising new technique for determination of fundamental stellar atmospheric parameters on the basis of comparison between the model generated synthetic spectra and observed stellar spectra.
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    ULTRAVIOLET STELLAR SPECTRAL CLASSIFICATION USING A MULTILEVEL TREE NEURAL NETWORK
    (Elsevier Science Ltd, 1995-01-25) Gulati, R.K; Gupta, R; Gothoskar, P; et.al
    Here we present a pattern classification technique based on an Artificial Neural Network (ANN) in a multi-level tree configuration to classify ultraviolet stellar spectra from the IUE Low-Dispersion Spectra Reference Atlas. Preliminary results of this technique show that 94% of the spectra have been classified correctly with an accuracy of one sub-class. A conventional 9~2 minimization scheme has also been applied to the data to compare the classification obtained from these schemes with that of the IUE catalog classification.
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    UV spectrum of λ boo
    (2015-01-25) Gerbaldi, M.; Gulati, R.K; Faraggiana, R.; Kurucz, R.L.
    Abstract. By using stellar computed atmospheric models with ATLAS9 and ATLAS12 codes, we compare fluxes in the ultra-violet domain with the one observed in low dispersion mode of the IUE satellite for the star λ Boo. We derive the chemical abundance of zinc and chromium from high dispersion IUE data by applying spectrum synthesis technique.