Unscented Hellinger distance between GMMs

The code calculates a metric between a pair of multivariate Gaussian Mixture Models.
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Actualizado 7 jun 2013

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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: http://vicos.fri.uni-lj.si/data/publications/KristanPR11.pdf)

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Matej Kristan (2024). Unscented Hellinger distance between GMMs (https://www.mathworks.com/matlabcentral/fileexchange/36164-unscented-hellinger-distance-between-gmms), MATLAB Central File Exchange. Recuperado .

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Versión Publicado Notas de la versión
1.2.0.0

There was an error in the visualization part. The visualization "/drawTools/"

1.0.0.0