Publication:
Artificial Neural Networks

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cris.virtualsource.department067e160e-cc13-4bdb-b777-9308f5232833
cris.virtualsource.department5f555019-6782-407e-a276-7f69d7bed685
cris.virtualsource.departmentb73643aa-b9b2-4382-bec8-e989e9ca2a00
cris.virtualsource.orcid067e160e-cc13-4bdb-b777-9308f5232833
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cris.virtualsource.orcidb73643aa-b9b2-4382-bec8-e989e9ca2a00
dc.contributor.authorGulko, Illya
dc.contributor.authorKirichenko, V.E.
dc.contributor.authorIvanchenko, I.A.
dc.date.accessioned2017-07-06T07:30:01Z
dc.date.available2017-07-06T07:30:01Z
dc.date.issued2017
dc.description.abstractArtificial Neural Network is a mathematical model, made in the form of software or hardware, built on the principle of biological neural networks of living cells. The neural network is a system of connected processors interacting with each other. If you compare them with the biological analogue, you will understand that the artificial network and the network of neurons are almost the same things. These processors are usually simple (compared to a CPU used in a PC). Each network processor either receives signals for processing or sent it to other processors. But if they are connected in a huge network with controlled interaction, these «simple» processors in large quantities can complete incredibly complicated tasks.ru_RU
dc.identifier.citationGulko I. Artificial Neural Networks / Illya Gulko, V.E.Kirichenko, I.A.Ivanchenko // Розширюючи обрії : зб. тез 12-го міжнародного форуму студентів і молодих учених, 20-21 квітня, 2017 р. [Електронний ресурс]. Т. 2. - 2017. - P. 123.ru_RU
dc.identifier.urihttp://ir.nmu.org.ua/handle/123456789/149586
dc.language.isoenru_RU
dc.publisherВидавництво НГУru_RU
dc.subjectArtificial Neural Networksru_RU
dc.subjectИскусственные нейронные сетиru_RU
dc.titleArtificial Neural Networksru_RU
dc.typeArticleru_RU
dspace.entity.typePublication

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