Majorization inequalities for strongly f-divergences with applications

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Titel: Majorization inequalities for strongly f-divergences with applications
Autoren: Ivelić Bradanović, Slavica
Verlagsinformationen: 2023.
Publikationsjahr: 2023
Schlagwörter: strongly convex functions, Csizar f-divergences, majorization inequalities
Beschreibung: Nonnegative measures of dissimilarity between pairs of probability measures are known as divergence measures. Numerous applications of these concept in different fields such as probability theory, statistics, information theory, signal processing etc. could be found in literature. One important class of divergence measures is defined by means of convex functions f , known as f-divergences or Csisz ́ar f-divergences. Recently, the concept of f-divergences for strongly convex functions with stronger properties is introduced. We derive new inequalities for strongly f-divergences and as outcome we obtain stronger estimates for some well known divergences as the Kullback-Leibler divergence, χ2-divergence, Hellinger divergence, Bhattacharya distance and Jeffreys distance.
Publikationsart: Conference object
Dokumentencode: edsair.dris...01492..d700a55b070e58039723d2c248e9b2ea
Datenbank: OpenAIRE
Beschreibung
Abstract:Nonnegative measures of dissimilarity between pairs of probability measures are known as divergence measures. Numerous applications of these concept in different fields such as probability theory, statistics, information theory, signal processing etc. could be found in literature. One important class of divergence measures is defined by means of convex functions f , known as f-divergences or Csisz ́ar f-divergences. Recently, the concept of f-divergences for strongly convex functions with stronger properties is introduced. We derive new inequalities for strongly f-divergences and as outcome we obtain stronger estimates for some well known divergences as the Kullback-Leibler divergence, χ2-divergence, Hellinger divergence, Bhattacharya distance and Jeffreys distance.