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dc.contributor.authorGarliauskas, Algirdas
dc.date.accessioned2023-09-18T20:22:49Z
dc.date.available2023-09-18T20:22:49Z
dc.date.issued2004
dc.identifier.issn0868-4952
dc.identifier.other(BIS)LBT02-000014425
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/149357
dc.description.abstractIn this paper, the main measure, an amount of information, of the information theory is analyzed and corrected. The three conceptions of the theory on the microstate, dissipation pathways, and self-organization levels with a tight connection to the statistical physics are discussed. The concepts of restricted information were introduced as well as the proof of uniqueness of the entropy function, when the probabilities are rational numbers, is presented. The artificial neural network (ANN) model for mapping the evaluation of transmitted information has been designed and experimentally approbated in the biological area.eng
dc.description.abstractStraipsnyje analizuojami ir tikslinami pagrindiniai informacijos teorijos matai ir informacijos kiekio įverčiai. Nagrinėjamos trys teorijos koncepcijos mikrobūsenų, disipacijos ir saviorganizacijos lygmenyse. Įrodytas entropijos funkcijos vienatiškumas aprėžtos informacijos atvejui. Remiantis dirbtinio neurotinklo modeliu atliktas eksperimentinis įvertinimas biologinės informacijos srityje.lit
dc.format.extentp. 475-488
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyMathSciNet
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.source.urihttp://iospress.metapress.com/app/home/contribution.asp?wasp=696be30a18c741df9016cb90ecf0b864&referrer=parent&backto=issue,4,9;journal,3,10;linkingpublicationresults,1:113362,1
dc.titleConceptions and modeling for transmitted information evaluation by ANN
dc.title.alternativePerduodamos informacijos įvertinimo koncepcijos ir modeliavimas dirbtiniais neurotinklais
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.references17
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionMatematikos ir informatikos institutas Vilniaus Gedimino technikos universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.subject.researchfieldN 001 - Matematika / Mathematics
dc.subject.researchfieldN 009 - Informatika / Computer science
dc.subject.enInformation theory
dc.subject.enEntropy
dc.subject.enInformation, amount of
dc.subject.enNeural networks, artificial
dcterms.sourcetitleInformatica
dc.description.issueno. 4
dc.description.volumeVol. 15
dc.identifier.doiVGT02-000010047
dc.identifier.doi000226037500004
dc.identifier.elaba5487131


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