Dirac Mixture Density Approximation Based on Minimization of the Weighted Cramer-von Mises Distance

@article{Schrempf2006DiracMD,
  title={Dirac Mixture Density Approximation Based on Minimization of the Weighted Cramer-von Mises Distance},
  author={Oliver C. Schrempf and Dietrich Brunn and Uwe D. Hanebeck},
  journal={2006 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems},
  year={2006},
  pages={512-517}
}
This paper proposes a systematic procedure for approximating arbitrary probability density functions by means of Dirac mixtures. For that purpose, a distance measure is required, which is in general not well defined for Dirac mixture densities. Hence, a distance measure comparing the corresponding cumulative distribution functions is employed. Here, we focus on the weighted Cramer-von Mises distance, a weighted integral quadratic distance measure, which is simple and intuitive. Since a closed… CONTINUE READING
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