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Features modeling with an $α$-stable distribution: Application to pattern recognition based on continuous belief functions

The aim of this paper is to show the interest in fitting features with an $\alpha$-stable distribution to classify imperfect data. The supervised pattern recognition is thus based on the theory of continuous belief functions, which is a way to consider imprecision and uncertainty of data... (read more)

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