Predicate data model in the form of a linear space

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dc.citation.epage54
dc.citation.issue4
dc.citation.spage51
dc.citation.volume8
dc.contributor.affiliationKharkiv National University of Radioelectronics
dc.contributor.authorShliakhov, V.
dc.contributor.authorChetverykov, G.
dc.contributor.authorBozhko, I.
dc.contributor.authorShliakhova, N.
dc.coverage.placenameLublin
dc.date.accessioned2020-02-28T09:27:47Z
dc.date.available2020-02-28T09:27:47Z
dc.date.created2019-06-26
dc.date.issued2019-06-26
dc.description.abstractThe restriction of the input set in the form of a positive cone of the space <L, R> is not always correct. For instance, while studying the organ of vision, people are limited not only to positive, but also to radiation with not very high energies, because excessively intense can disturb the visual organ. In this particular case, a convex body of a linear space is a fairly acceptable model of the set of input signals. Therefore, we consider linear predicates with this domain of definition.
dc.format.extent51-54
dc.format.pages4
dc.identifier.citationPredicate data model in the form of a linear space / V. Shliakhov, G. Chetverykov, I. Bozhko, N. Shliakhova // Econtechmod : scientific journal. — Lublin, 2019. — Vol 8. — No 4. — P. 51–54.
dc.identifier.citationenPredicate data model in the form of a linear space / V. Shliakhov, G. Chetverykov, I. Bozhko, N. Shliakhova // Econtechmod : scientific journal. — Lublin, 2019. — Vol 8. — No 4. — P. 51–54.
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/46306
dc.language.isoen
dc.relation.ispartofEcontechmod : scientific journal, 4 (8), 2019
dc.relation.references1. Maltsev A. 1973. Algebraic Systems”. SpringerVerlag Berlin Heidelberg, 320 p.
dc.relation.references2. Chetverikov G.G. , Vechirska I.Dtanyanskiy. S.S. 2014. The methods of algebra of finite predicates in the intellectual system of complex calculations of telecommunication companies. In: CriMiCo 2014, 24th International Crimean Conference Microwave and Telecommunication Technology, Sevastopol, 2014: 346–347.
dc.relation.references3. Mousavi S. M. H., Lyashenko V. 2017. Extracting Old Persian Cuneiform Font Out of Noisy Images (Handwritten or Inscription). In: IEEE 10th Iranian Conference on Machine Vision and Image Processing (MVIP), 241–246.
dc.relation.references4. Sharonova N., Doroshenko A., Cherednichenko O. 2018. Issues of fact-based information analysis . In: Proc. of the International Conference on Computational linguistics and intelligent systems. Volume 2136: 11–19
dc.relation.references5. Kosar O., Shakhovska N. 2018. An Overview of Denoising Methods for Different Types of Noises Present on Graphic Images. In: Conference on Computer Science and Information Technologies CSIT 2018: 38–47.
dc.relation.references6. Khairova N., Petrasova S., Gautam Ajit Pratap Singh. 2015. The logic and linguistic model for automatic extraction of collocation similarity. Econtechmod. Vol. 4. No. 4: 43–48.
dc.relation.referencesen1. Maltsev A. 1973. Algebraic Systems". SpringerVerlag Berlin Heidelberg, 320 p.
dc.relation.referencesen2. Chetverikov G.G. , Vechirska I.Dtanyanskiy. S.S. 2014. The methods of algebra of finite predicates in the intellectual system of complex calculations of telecommunication companies. In: CriMiCo 2014, 24th International Crimean Conference Microwave and Telecommunication Technology, Sevastopol, 2014: 346–347.
dc.relation.referencesen3. Mousavi S. M. H., Lyashenko V. 2017. Extracting Old Persian Cuneiform Font Out of Noisy Images (Handwritten or Inscription). In: IEEE 10th Iranian Conference on Machine Vision and Image Processing (MVIP), 241–246.
dc.relation.referencesen4. Sharonova N., Doroshenko A., Cherednichenko O. 2018. Issues of fact-based information analysis . In: Proc. of the International Conference on Computational linguistics and intelligent systems. Volume 2136: 11–19
dc.relation.referencesen5. Kosar O., Shakhovska N. 2018. An Overview of Denoising Methods for Different Types of Noises Present on Graphic Images. In: Conference on Computer Science and Information Technologies CSIT 2018: 38–47.
dc.relation.referencesen6. Khairova N., Petrasova S., Gautam Ajit Pratap Singh. 2015. The logic and linguistic model for automatic extraction of collocation similarity. Econtechmod. Vol. 4. No. 4: 43–48.
dc.rights.holder© Copyright by Lviv Polytechnic National University 2019
dc.rights.holder© Copyright by University of Engineering and Economics in Rzeszów 2019
dc.subjectpredicate model
dc.subjectlinear space
dc.subjectpredicate algebra
dc.subjectalgebraic structure
dc.titlePredicate data model in the form of a linear space
dc.typeArticle

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Econtechmod. – 2019. – Vol. 8, No. 4