Title :
Infinitely Many Information Inequalities
Author_Institution :
Acad. of Sci. of the Czech Republic, Prague
Abstract :
When finite, Shannon entropies of all sub vectors of a random vector are considered for the coordinates of an entropic point in Euclidean space. A linear combination of the coordinates gives rise to an unconstrained information inequality if it is nonnegative for all entropic points. With at least four variables no finite set of linear combinations generates all such inequalities. This is proved by constructing explicitly an infinite sequence of new linear information inequalities and a curve in a special geometric position to the halfspaces defined by the inequalities. The inequalities are constructed recurrently by adhesive pasting of restrictions of polymatroids and the curve ranges in the closure of a set of the entropic points.
Keywords :
entropy; matrix algebra; vectors; Euclidean space; Shannon entropy; information inequality; polymatroids; random vector; Automation; Cramer-Rao bounds; Entropy; Information analysis; Information theory; Shape; Vectors;
Conference_Titel :
Information Theory, 2007. ISIT 2007. IEEE International Symposium on
Conference_Location :
Nice
Print_ISBN :
978-1-4244-1397-3
DOI :
10.1109/ISIT.2007.4557201