Estimating complexity of classification tasks using neurocomputers technology

dc.contributor.authorBudnyk, Ivan
dc.contributor.authorChebira, Abdennasser
dc.contributor.authorMadani, Kurosh
dc.date.accessioned2018-12-05T09:43:30Z
dc.date.available2018-12-05T09:43:30Z
dc.date.issued2009
dc.description.abstractThis paper presents an alternative approach for estimating task complexity. Construction of a self-organizing neural tree structure, following the paradigm “divide and rule”, requires knowledge about task complexity. Our aim is to determine complexity indicator function and to hallmark its’ main properties. A new approach uses IBM © Zero Instruction Set Computer (ZISC-036 ®) and applies for a range of the different classification tasks.uk_UA
dc.identifier.citationBudnyk, І. Estimating complexity of classification tasks using neurocomputers technology [Text] / Ivan Budnyk, Abdennasser Chebira, Kurosh Madani // Computing = Комп’ютинг. - 2009. - Vol. 8, is. 1. - P. 43-52.uk_UA
dc.identifier.urihttp://dspace.tneu.edu.ua/handle/316497/32007
dc.publisherТНЕУuk_UA
dc.subjectIBM © Zero Instruction Set Computer (ZISC-036 ®) Neurocomputeruk_UA
dc.subjectNeural tree modular architectureuk_UA
dc.subjectT- DTSuk_UA
dc.subjectDNA (Deoxyribonucleic acid)uk_UA
dc.subjectRNA (Ribonucleic acid)uk_UA
dc.subjectexonuk_UA
dc.subjectintronuk_UA
dc.subjectSplice junctions problemuk_UA
dc.subjectTic-tac-toe endgame problemuk_UA
dc.titleEstimating complexity of classification tasks using neurocomputers technologyuk_UA
dc.typeArticleuk_UA

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