Formation of Weighting Coefficients in an Artificial Neural Network Based on the Memristive Effect in Metal–Oxide–Metal Nanostructures
- 作者: Antonov I.1, Belov A.1, Mikhaylov A.1, Morozov O.1, Ovchinnikov P.1
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隶属关系:
- Lobachevsky State University of Nizhny Novgorod
- 期: 卷 63, 编号 8 (2018)
- 页面: 950-957
- 栏目: Novel Radio Systems and Elements
- URL: https://journals.rcsi.science/1064-2269/article/view/200091
- DOI: https://doi.org/10.1134/S106422691808003X
- ID: 200091
如何引用文章
详细
An approach to formation and training of an artificial neural network (ANN) based on thin-film memristive metal–oxide–metal nanostructures, which exhibit the effect of bipolar resistive switching, has been proposed. An experimental electric circuit of a small-sized ANN (a two-layer perceptron with 32 memristive elements) has been constructed. An algorithm for formation of weighting coefficients (ANN training), which takes into account probable spread of technological parameters of memristive structures has been developed.
作者简介
I. Antonov
Lobachevsky State University of Nizhny Novgorod
Email: oa_morozov@nifti.unn.ru
俄罗斯联邦, Nizhny Novgorod, 603950
A. Belov
Lobachevsky State University of Nizhny Novgorod
Email: oa_morozov@nifti.unn.ru
俄罗斯联邦, Nizhny Novgorod, 603950
A. Mikhaylov
Lobachevsky State University of Nizhny Novgorod
Email: oa_morozov@nifti.unn.ru
俄罗斯联邦, Nizhny Novgorod, 603950
O. Morozov
Lobachevsky State University of Nizhny Novgorod
编辑信件的主要联系方式.
Email: oa_morozov@nifti.unn.ru
俄罗斯联邦, Nizhny Novgorod, 603950
P. Ovchinnikov
Lobachevsky State University of Nizhny Novgorod
Email: oa_morozov@nifti.unn.ru
俄罗斯联邦, Nizhny Novgorod, 603950