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Issue No.01 - January (1980 vol.2)
pp: 61-67
Dimitri Kazakos , Department of Electrical Engineering, State University of New York at Buffalo, Amherst, NY 14260.
ABSTRACT
The problem of approximating a probability density function by a simpler one is considered from a decision theory viewpoint. Among the family of candidate approximating densities, we seek the one that is most difficult to discriminate from the original. This formulation leads naturaliy to the density at the smallest Bhattacharyya distance. The resulting optimization problem is analyzed in detail.
CITATION
Dimitri Kazakos, "A Decision Theory Approach to the Approximation of Discrete Probability Densities", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.2, no. 1, pp. 61-67, January 1980, doi:10.1109/TPAMI.1980.4766971
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