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A concavity property for the reciprocal of Fisher information and its consequences on Costa's EPI

Abstract

We prove that the reciprocal of Fisher information of a log-concave probability density XX in Rn{\bf{R}}^n is concave in tt with respect to the addition of a Gaussian noise Zt=N(0,tIn)Z_t = N(0, tI_n). As a byproduct of this result we show that the third derivative of the entropy power of a log-concave probability density XX in Rn{\bf{R}}^n is nonnegative in tt with respect to the addition of a Gaussian noise ZtZ_t. For log-concave densities this improves the well-known Costa's concavity property of the entropy power

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