Abstract
The IRAS Low Resolution Spectrometer (LRS) covered the spectral region from 7µm to 23µm, and an Atlas was produced containing 5425 spectra. Most of the spectra were associated with evolved stars, including over 3000 spectra from the dust shells around O-rich stars. When Artificial Intelligence techniques were applied to the dataset, a new classification was derived. A scheme with 77 classes, grouped into 9 metaclasses, resulted, and for those types of spectra which were well represented in the initial dataset (i.e. the evolved stars) a very subtle classification was derived, often using line shapes, relative line strengths, or the presence of additional weak features.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Cheeseman, P., Stutz, J., Self, M., Taylor, W., Goebel, J., Volk, K., and Walker, H.: 1989,NASA R,,,,Printer,rror,,,ar,in,,up,,,,,,ef. Publ. 1217,
Goebel, J., Volk, K., Walker, H., Gerbault, F., Cheeseman, P., Self, M., Stutz, J., and Taylor, W.: 1989,Astron. Astrophys. 222, L5
IRAS Catalogs and Atlases: Atlas of Low Resolution Spectra: 1986, IRAS Science Team, prepared by F. M. Olnon and E. Raimond. (Astron. Astrophys. Suppl. 65, 607)
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Walker, H.J. Using Artificial Intelligence techniques to classify IRAS LRS spectra of evolved stars. Astrophys Space Sci 217, 139–140 (1994). https://doi.org/10.1007/BF00990040
Issue Date:
DOI: https://doi.org/10.1007/BF00990040