On the Decrease Rate of the Non-Gaussianness of the Sum of Independent Random Variables

dc.creatorBinia, Jacob
dc.date2006-12-17
dc.date.accessioned2026-07-07T08:16:52Z
dc.date.available2026-07-07T08:16:52Z
dc.descriptionSeveral proofs of the monotonicity of the non-Gaussianness (divergence with respect to a Gaussian random variable with identical second order statistics) of the sum of n independent and identically distributed (i.i.d.) random variables were published. We give an upper bound on the decrease rate of the non-Gaussianness which is proportional to the inverse of n, for large n. The proof is based on the relationship between non-Gaussianness and minimum mean-square error (MMSE) and causal minimum mean-square error (CMMSE) in the time-continuous Gaussian channel.
dc.descriptionSubmitted to the Trasactions of the IEEE on Information Theory
dc.identifierhttps://arxiv.org/abs/cs/0612080
dc.identifierhttp://arxiv.org/abs/cs/0612080
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/133938
dc.subjectInformation Theory
dc.titleOn the Decrease Rate of the Non-Gaussianness of the Sum of Independent Random Variables
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