منابع مشابه
Non-linear Information Inequalities
We construct non-linear information inequalities from Matúš’ infinite series of linear information inequalities. Each single non-linear inequality is sufficiently strong to prove that the closure of the set of all entropy functions is not polyhedral for four or more random variables, a fact that was already established using the series of linear inequalities. To the best of our knowledge, they ...
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We present a framework for information inequalities, namely, inequalities involving only Shannon’s information measures, for discrete random variables. A region in IR2 1, denoted by , is identified to be the origin of all information inequalities involving n random variables in the sense that all such inequalities are partial characterizations of . A product from this framework is a simple calc...
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We consider a random variable X that takes values in a (possibly infinite-dimensional) topological vector space X . We show that, with respect to an appropriate “normal distance” on X , concentration inequalities for linear and non-linear functions ofX are equivalent. This normal distance corresponds naturally to the concentration rate in classical concentration results such as Gaussian concent...
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چکیده ندارد.
15 صفحه اولOn Fisher Information Inequalities and Score Functions in Non-invertible Linear Systems
In this note, we review score functions properties and discuss inequalities on the Fisher Information Matrix of a random vector subjected to linear non-invertible transformations. We give alternate derivations of results previously published in [6] and provide new interpretations of the cases of equality.
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ژورنال
عنوان ژورنال: Entropy
سال: 2008
ISSN: 1099-4300
DOI: 10.3390/e10040765