Kullback–Leibler Divergence and Mutual Information of Partitions in Product MV Algebras
Dagmar Markechová, Beloslav Riečan
Abstract
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Dagmar Markechová, Beloslav Riečan
Abstract
Open-access reader
The purpose of the paper is to introduce, using the known results concerning the entropy in product MV algebras, the concepts of mutual information and Kullback–Leibler divergence for the case of product MV algebras and examine algebraic properties of the proposed measures. In particular, a convexity of Kullback–Leibler divergence with respect to states in product MV algebras is proved, and chain rules for mutual information and Kullback–Leibler divergence are established. In addition, the data processing inequality for conditionally independent partitions in product MV algebras is proved.
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The purpose of the paper is to introduce, using the known results concerning the entropy in product MV algebras, the concepts of mutual information and Kullback–Leibler divergence for the case of product MV algebras and examine algebraic properties of the proposed measures. In particular, a convexity of Kullback–Leibler divergence with respect to states in product MV algebras is proved, and chain rules for mutual information and Kullback–Leibler divergence are established. In addition, the data processing inequality for conditionally independent partitions in product MV algebras is proved.
Key concepts: Kullback–Leibler divergence, Mutual information, Divergence (linguistics), Total correlation, Mathematics, Convexity, Product (mathematics), Entropy (arrow of time)