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Article Dans Une Revue IEEE Signal Processing Letters Année : 2023

Exact Rényi and Kullback-Leibler Divergences Between Multivariate t-Distributions

Résumé

In this letter, we propose a closed-form expression of the Rényi divergence (RD) of order β between two zero-mean real multivariate t-distributions (MTDs). Such distribution has been deployed in several signal and image processing applications where heavy-tailed distribution is well-suited. Based on the computation of the multiple integral involved in the RD, the expression of the divergence is provided without resorting to the conventional time-consuming Monte Carlo (MC) integration technique. In addition, the Kullback-Leibler divergence (KLD) is deduced from RD. Finally, a comparison is made between the MC method and the numerical value of the RD expression to show how the former gives close approximations to the latter.
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Dates et versions

hal-04447567 , version 1 (08-02-2024)

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Nizar Bouhlel, David Rousseau. Exact Rényi and Kullback-Leibler Divergences Between Multivariate t-Distributions. IEEE Signal Processing Letters, 2023, 30, pp.1672-1676. ⟨10.1109/LSP.2023.3324594⟩. ⟨hal-04447567⟩
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