Here are the best efforts and results from the literature:
Best
- Weaver, et al 1997: Accurate Two-dimensional Classification of Stellar Spectra with Artificial Neural Networks
- Bailer-Jones 2002: Automated Stellar Classification for Large Surveys: A Review of Methods and Results
- Re Fiorentin, et al 2007: Estimation of stellar atmospheric parameters from SDSS/SEGUE spectra
- Allende Prieto 2004: Automated analysis of stellar spectra
- Allende Prieto 2003: An automated system to classify stellar spectra - I
- Bailer-Jones, 1997: Neural Network Classification of Stellar Spectra
- Bailer-Jones, et al 1997: Physical parametrization of stellar spectra - The neural network approach
- Bailer-Jones, et al 1998: Automated classification of stellar spectra - II. Two-dimensional classification with neural networks and principal components analysis
- Recio-Blanco, et al. 2006: Automated derivation of stellar atmospheric parameters and chemical abundances: the MATISSE algorithm
Information on PCA, SVM and Neural Networks
- Bailer-Jones, et al 2002: An Introduction to Artificial Neural Networks
- Jonathon Shlens, 2009: A Tutorial on Principal Component Analysis
- Wikipedia article on SVM: Support vector machine
- Chih-Wei Hsu, et al. 2009: A Practical Guide to Support Vector Classification
Software
- Modular toolkit for Data Processing to perform PCA and the like in python easily.
- LIBSVM -- A Library for Support Vector Machines includes python bindings for use in python
- Simulated Annealing: an optimization algorithm for finding global minima for "difficult" functions. The advantage of these is that they are able to escape local minima.
Related Things
- Stellar synthetic spectroscopy in the VO era - Slides on synthetic spectra and related topics
- Libraries of stellar spectra
- Synthetic spectra (overview)
- Kevin R. Covey's "The Hammer" in IDL
- SPTCLASS: SPecTral CLASSificator code
MK Standard Stars
- Munari & Sordo 2005: Available libraries of observed spectra.
- Valdes et al 2004: The Indo-US Library of Coudé Feed Stellar Spectra Actual data at http://www.noao.edu/cflib/
- Garcia, 1989: A list of MK standard stars
- Smarts 1.5m Standards courtesy of Fred Walter
- MK Standard Stars from the CTIO 1.5m (Smarts, same as the above telescope) from R. O. Gray
Synthetic Spectra
- Coelho, et al 2005: A library of high resolution synthetic stellar spectra from 300 nm to 1.8 μm with solar and α-enhanced composition
- Munari et al 2005: An extensive library of 2500 10 500 Å synthetic spectra
- Brott & Hauschildt 2005: A PHOENIX Model Atmosphere Grid for Gaia
- New high resolution synthetic stellar libraries for the Gaia Mission
- A grid of MARCS model atmospheres for late-type stars. I. Methods and general properties
- Fiorella Castelli's Web site
Other Similar Papers
- Katz, et al. 1998: On-line determination of stellar atmospheric parameters T_eff, log g, [Fe/H] from ELODIE echelle spectra. I. The method
- Allende Prieto, et al 2008: The Segue Stellar Parameter Pipeline. III. Comparison with High-Resolution Spectroscopy of Sdss/segue Field Stars
- von Hippel, et al 2003: Automated Stellar Spectral Classification and Parameter-Ization for the Masses
- Bailer-Jones 2000: Stellar parameters from very low resolution spectra and medium band filters. T_eff, log g and [M/H] using neural networks
- Willemsen, et al 2005: Analysis of medium resolution spectra by automated methods - Application to M 55 and . Centauri
- Koleva, et al. 2009: ULySS: A Full Spectrum Fitting Package
- Willemsen, et al 2003: Automated determination of stellar parameters from simulated dispersed images for DIVA