Browsing by Author "Singh, S. Jotin"

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    Cross-checking reliability of some available stellar spectral libraries using artificial neural networks
    (Stellar Populations as Building Blocks of Galaxies Proceedings IAU Symposium, 2006-06-25) Gupta, Ranjan; Singh, S. Jotin; Singh, Harinder P
    Cross-checking the reliability of various stellar spectral databases is an important and desirable exercise. Since number of stars in various databases have no known spectral types and some of the libraries do not have complete coverage resulting in gaps. We use an automated classification scheme based on Artificial Neural Networks (ANN) to cross-classify stars in the Indo-US stellar spectral library (Valdes et al. 2004), JHC (Jacoby, Hunter & Christian 1984), ELODIE spectra (Moultaka et al. 2004) and STELIB (Le Borgne et al. 2003). We have also examined the effects of over-training and over-fitting on the classification efficiency of a Neural Network. It is hoped that such a automated data analysis and validation technique will be useful in the future.
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    Filling Gaps in Indo-US Stellar Spectral Library using Principal Component Analysis
    (Stellar Populations as Building Blocks of Galaxies Proceedings IAU Symposium, 2006-07-12) Singh, Harinder P; Singh, S. Jotin; Gupta, Ranjan; et
    The Indo-US coud´e feed stellar spectral library (CFLIB) published recently by Valdes et al. (2004) contains spectra of 1273 stars in the spectral region 3460 to 9464 ˚A at a resolution of 1 ˚A. About 500 stars in this database have gaps ranging from a few ˚A to several tens of ˚A in this wavelength range. We use a variation of Principal Component Analysis (PCA) technique to fill gaps of up to 5˚A in a subset of spectra from the CFLIB. We hope to exploit the full potential of the scheme and attempt to fill larger gaps in stellar spectra in a subsequent study.