On the Distribution of the Information Density of Gaussian Random Vectors: Explicit Formulas and Tight Approximations

On the Distribution of the Information Density of Gaussian Random Vectors: Explicit Formulas and Tight Approximations

Based on the canonical correlation analysis, we derive series representations of the probability density function (PDF) and the cumulative distribution function (CDF) of the information density of arbitrary Gaussian random vectors as well as a general formula to calculate the central moments. Using...

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Bibliographic Details
Main Authors: Jonathan E. W. Huffmann, Martin Mittelbach
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Entropy
Subjects:
information density
information spectrum
probability density function
cumulative distribution function
central moments
Gaussian random vector
Online Access:https://www.mdpi.com/1099-4300/24/7/924

Internet

https://www.mdpi.com/1099-4300/24/7/924

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