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Unscented Hellinger distance between GMMs

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The code calculates a metric between a pair of multivariate Gaussian Mixture Models.



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This is a demo code for the unscented Hellinger distance between a pair of Gaussian mixture models. The code follows the derivation of the multivariate unscented Hellinger distance introduced in [1]. Unlike the Kullback-Leibler divergence, the Hellinger distance is a proper metric between the distributions and is constrained to interval (0,1) with 0 meaning complete similarity and 1 complete dissimilarity.

[1] M. Kristan, A. Leonardis, D. Skočaj, "Multivariate online Kernel Density Estimation", Pattern Recognition, 2011. (url:

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