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Minimum entropy of error principle in estimation
Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic.
Luleå tekniska universitet.
Institute of Information Theory and Automation, Academy of Sciences of the Czech Republic.
1994 (English)In: Information Sciences, ISSN 0020-0255, E-ISSN 1872-6291, Vol. 79, no 1-2, p. 123-144Article in journal (Refereed) Published
Abstract [en]

The principle of minimum error entropy estimation as found in the work of Weidemann and Stear is reformulated as a problem of finding optimum locations of probability densities in a given mixture such that the resulting (differential) entropy is minimized. New results concerning the entropy lower bound are derived. Continuity of the entropy and attaining the minimum entropy are proved in the case where the mixture is finite. Some other examples and situations, in particular that of symmetric unimodal densities, are studied in more detail

Place, publisher, year, edition, pages
1994. Vol. 79, no 1-2, p. 123-144
National Category
Mathematical Analysis
Research subject
Mathematics
Identifiers
URN: urn:nbn:se:ltu:diva-5107Local ID: 32179c80-0d70-11de-9d3e-000ea68e967bOAI: oai:DiVA.org:ltu-5107DiVA: diva2:977981
Note
Godkänd; 1994; 20090310 (andbra)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-21Bibliographically approved

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