REPOZYTORIUM UNIWERSYTETU
W BIAŁYMSTOKU
UwB

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dc.contributor.authorZhang, Bo-
dc.contributor.authorNakamura, Yatsuka-
dc.date.accessioned2026-10-30T07:19:26Z-
dc.date.available2026-10-30T07:19:26Z-
dc.date.issued2007-
dc.identifier.citationFormalized Mathematics, Volume 15, Issue 3, Pages 111-119pl
dc.identifier.issn1426-2630-
dc.identifier.urihttp://hdl.handle.net/11320/21376-
dc.description.abstractIn this article we mainly define the information entropy [3], [11] and prove some its basic properties. First, we discuss some properties on four kinds of transformation functions between vector and matrix. The transformation functions are LineVec2Mx, ColVec2Mx, Vec2DiagMx and Mx2FinS. Mx2FinS is a horizontal concatenation operator for a given matrix, treating rows of the given matrix as finite sequences, yielding a new finite sequence by horizontally joining each row of the given matrix in order to index. Then we define each concept of information entropy for a probability sequence and two kinds of probability matrices, joint and conditional, that are defined in article [25]. Further, we discuss some properties of information entropy including Shannon's lemma, maximum property, additivity and super-additivity properties.pl
dc.language.isoenpl
dc.publisherUniversity of Białystokpl
dc.rightsAttribution-ShareAlike 4.0 International (CC BY-SA 4.0)-
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/-
dc.titleDefinition and some Properties of Information Entropypl
dc.typeArticlepl
dc.rights.holder© 2008 Bo Zhang, Yatsuka Nakamura, published by University of Białystokpl
dc.rights.holderThis work is licensed under the Creative Commons License.pl
dc.identifier.doi10. 2478/v10037-007-0012-9-
dc.description.AffiliationBo Zhang - Shinshu University, Nagano, Japanpl
dc.description.AffiliationYatsuka Nakamura - Shinshu University, Nagano, Japanpl
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dc.description.volume15pl
dc.description.issue3pl
dc.description.firstpage111pl
dc.description.lastpage119pl
dc.identifier.citation2Formalized Mathematicspl
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