Application of the volume learning algorithm artificial neural networks for recognition of the type of interaction between neurons from their cross-correlation histograms
dc.contributor.author | Kovalishyn, V. V. | |
dc.contributor.author | Tetko, I. V. | |
dc.date.accessioned | 2024-04-22T06:32:37Z | |
dc.date.available | 2024-04-22T06:32:37Z | |
dc.date.issued | 2005 | |
dc.description.abstract | An algorithm based on two types artificial neural networks (ANNs) is proposed. The first network is an associative ANN while the second network is a Self-Organizing Map of Kohonen. The results for a test set are similar to the performance of our previous expert system algorithm developed with Group Method of Data Handling (GMDH). However, while GMDH uses indices derived using the expert knowledge (and thus require considerable time and resources) the VLA process initial raw data. | |
dc.format.pagerange | Pp. 48-56 | |
dc.identifier.citation | Kovalishyn, V. V. Application of the volume learning algorithm artificial neural networks for recognition of the type of interaction between neurons from their cross-correlation histograms / Kovalishyn V. V., Tetko I. V. // Системні дослідження та інформаційні технології : міжнародний науково-технічний журнал. – 2005. – № 3. – С. 48-56. – Бібліогр.: 20 назви. | |
dc.identifier.issn | 1681–6048 | |
dc.identifier.uri | https://ela.kpi.ua/handle/123456789/66370 | |
dc.language.iso | en | |
dc.publisher | КПІ ім. Ігоря Сікорського | |
dc.publisher.place | Київ | |
dc.relation.ispartof | Системні дослідження та інформаційні технології: міжнародний науково-технічний журнал, № 3 | |
dc.subject.udc | 519.688 | |
dc.title | Application of the volume learning algorithm artificial neural networks for recognition of the type of interaction between neurons from their cross-correlation histograms | |
dc.type | Article |
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