Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Author: search.filters.author.Karacali, BilgeSubject: search.filters.subject.Conditional Entropy

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  • Conference Object
    Ortak Bilgi Miktarının Modelden-Baǧımsız ve Hızlı Hesaplanması için Yeni Yöntemler
    (IEEE, 2018) Cagdas, Serhat; Karacali, Bilge
    In this study, two new approaches are proposed to calculate mutual information between two random variables from data. These approaches are constructed in a way to use the properties of the differential entropy under linear transformations and to try to minimize conditional entropy in a model-free manner. In comparisons with a widely used mutual information estimator, the Kraskov method, the methods that we termed as unit vector parametrization and data fitting based estimators, offered an advantage in terms of computation speed.