Title :
Monotonic Decrease of the Non-Gaussianness of the Sum of Independent Random Variables: A Simple Proof
Author :
Tulino, Antonia M. ; Verdu, Sergio
Author_Institution :
Dept. of Electr. Eng., Univ. di Napoli
Abstract :
Artstein, Ball, Barthe, and Naor have recently shown that the non-Gaussianness (divergence with respect to a Gaussian random variable with identical first and second moments) of the sum of independent and identically distributed (i.i.d.) random variables is monotonically nonincreasing. We give a simplified proof using the relationship between non-Gaussianness and minimum mean-square error (MMSE) in Gaussian channels. As Artstein , we also deal with the more general setting of nonidentically distributed random variables
Keywords :
Gaussian channels; least mean squares methods; Gaussian channel; MMSE; independent-identically distributed random variable; minimum mean-square error; Convolution; Entropy; Fasteners; Functional analysis; Gaussian channels; Power measurement; Random variables; Signal to noise ratio; Central limit theorem; differential entropy; divergence; entropy power inequality; minimum mean-square error (MMSE); non-Gaussianness; relative entropy;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2006.880066