dc.contributor.author | VARHACH, Oleh | |
dc.contributor.author | KUGAI, Kseniia | |
dc.date.accessioned | 2021-06-23T12:21:06Z | |
dc.date.available | 2021-06-23T12:21:06Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | ȚURCAN, Ana. Neural network operating peculiarities. In: Conferinţa Tehnico-Ştiinţifică a Studenţilor, Masteranzilor şi Doctoranzilor, Universitatea Tehnică a Moldovei, 23-25 martie, 2021. Chişinău, 2021, vol. 1, pp. 264-267. ISBN 978-9975-45-699-9. | en_US |
dc.identifier.isbn | 978-9975-45-699-9 | |
dc.identifier.uri | http://repository.utm.md/handle/5014/16213 | |
dc.description.abstract | The article analyzes operating peculiarities of the standard neural network for a multilayer perceptron. The network structure and the principle of inverse error propagation algorithm operation are described. The article deals with the notions of artificial neural networks and deep structured learning. Neural networks are the basis of a new and interesting area – deep structured learning. The work covers basic concepts, as well as some code and math, which can help understand and build simple neural networks. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universitatea Tehnică a Moldovei | en_US |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | * |
dc.subject | algorithm | en_US |
dc.subject | deep structured learning | en_US |
dc.subject | neuron | en_US |
dc.subject | multilayer perceptron | en_US |
dc.title | Neural network operating peculiarities | en_US |
dc.type | Article | en_US |
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