International Symposium on Methodologies for Intelligent Systems

ISMIS 2005: Foundations of Intelligent Systems pp 485-493

A Probabilistic Approach to Finding Geometric Objects in Spatial Datasets of the Milky Way

  • Jon Purnell
  • Malik Magdon-Ismail
  • Heidi Jo Newberg
Conference paper

DOI: 10.1007/11425274_50

Volume 3488 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Purnell J., Magdon-Ismail M., Newberg H.J. (2005) A Probabilistic Approach to Finding Geometric Objects in Spatial Datasets of the Milky Way. In: Hacid MS., Murray N.V., Raś Z.W., Tsumoto S. (eds) Foundations of Intelligent Systems. ISMIS 2005. Lecture Notes in Computer Science, vol 3488. Springer, Berlin, Heidelberg

Abstract

Data from the Sloan Digital Sky Survey has given evidence of structures within the Milky Way halo from other nearby galaxies. Both the halo and these structures are approximated by densities based on geometric objects. A model of the data is formed by a mixture of geometric densities. By using an EM-style algorithm, we optimize the parameters of our model in order to separate out these structures from the data and thus obtain an accurate dataset of the Milky Way.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Jon Purnell
    • 1
  • Malik Magdon-Ismail
    • 1
  • Heidi Jo Newberg
    • 1
  1. 1.Rensselaer Polytechnic Institute