Impact of defects on multilayer artificial feed forward neural network operability
Автор: Marshakov Daniil V., Fatkhi Vladimir A.
Журнал: Вестник Донского государственного технического университета @vestnik-donstu
Рубрика: Технические науки
Статья в выпуске: 2 (53) т.11, 2011 года.
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Impact of buried layer likely defects on the performance of the multilayer feedforward artificial neural network is investigated. Dimensions of estimation of the correct network operation by pattern recognition are offered.
Fault tolerance, feedforward neural network, indices of correct recognition, artificial recognition
Короткий адрес: https://sciup.org/14249533
IDR: 14249533
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