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Kernel density estimation on the Siegel space applied to radar processing

Abstract : Main techniques of probability density estimation on Riemannian manifolds are reviewed in the case of the Siegel space. For computational reasons we chose to focus on the kernel density estimation. The main result of the paper is the expression of Pelletier's kernel density estimator. The method is applied to density estimation of reflection coefficients from radar observations.
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https://hal.archives-ouvertes.fr/hal-01344910
Contributor : Emmanuel Chevallier Connect in order to contact the contributor
Submitted on : Wednesday, July 13, 2016 - 8:55:51 PM
Last modification on : Monday, April 4, 2022 - 10:38:02 AM

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kernelSiegel.pdf
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  • HAL Id : hal-01344910, version 2

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Emmanuel Chevallier, Frédéric Barbaresco, Jesus Angulo. Kernel density estimation on the Siegel space applied to radar processing. 2016. ⟨hal-01344910v2⟩

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