| DC Field | Value | Language |
|---|
| dc.contributor.author | Dovguchits, S. M. | - |
| dc.date.accessioned | 2016-10-21T06:49:38Z | - |
| dc.date.accessioned | 2017-07-17T09:31:07Z | - |
| dc.date.available | 2016-10-21T06:49:38Z | - |
| dc.date.available | 2017-07-17T09:31:07Z | - |
| dc.date.issued | 2013 | - |
| dc.identifier.citation | Dovguchits, S. M. Artificial neural networks / S. M. Dovguchits // Моделирование, компьютерное проектирование и технология производства электронных средств : сборник материалов 49-й научной конференции аспирантов, магистрантов и студентов, Минск, 6–10 мая 2013 года / Белорусский государственный университет информатики и радиоэлектроники ; редкол.: Боднарь И. В. [и др.]. – Минск, 2013. – С. 206–207. | ru_RU |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/9546 | - |
| dc.description.abstract | A traditional digital computer does many tasks very well. It's quite fast, and it does exactly what you tell it to do.
Unfortunately, it can't help you when you yourself don't fully understand the problem you want to be solved. Even worse, standard
algorithms don't deal well with noisy or incomplete data, yet in the real world, that's frequently the only kind available. One answer is
to use an artificial neural network (ANN), a computing system that can learn on its own. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | БГУИР | ru_RU |
| dc.subject | материалы конференций | ru_RU |
| dc.subject | artificial neural networks | ru_RU |
| dc.title | Artificial neural networks | ru_RU |
| dc.type | Article | ru_RU |
| Appears in Collections: | Моделирование, компьютерное проектирование и технология производства электронных систем : материалы 49-й научной конференции аспирантов, магистрантов и студентов (2013)
|
