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The wave model of artificial neural network

The article deals with the modeling of artificial neural networks as a system of information transmission. The analysis of the existing theoretical approaches to the optimization of the structure and training of neural networks is carried out. The proposed model is based on the commonality of decodi...

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Egile Nagusiak: Vershkov, N. A., Вершков, Н. А., Kuchukov, V. A., Кучуков, В. А., Kuchukova, N. N., Кучукова, Н. Н., Babenko, M. G., Бабенко, М. Г.
Formatua: Статья
Hizkuntza:English
Argitaratua: Institute of Electrical and Electronics Engineers Inc. 2020
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Sarrera elektronikoa:https://dspace.ncfu.ru/handle/20.500.12258/12084
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spelling ir-20.500.12258-120842020-07-29T09:40:28Z The wave model of artificial neural network Vershkov, N. A. Вершков, Н. А. Kuchukov, V. A. Кучуков, В. А. Kuchukova, N. N. Кучукова, Н. Н. Babenko, M. G. Бабенко, М. Г. Artificial neural network Correlation function Spectral analysis Data communication systems The article deals with the modeling of artificial neural networks as a system of information transmission. The analysis of the existing theoretical approaches to the optimization of the structure and training of neural networks is carried out. The proposed model is based on the commonality of decoding processes in information transmission systems and clustering processes in neural networks. In the process of building a neuron model, we consider the well-known problem of determining the bandwidth capacity of the communication channel with noise in the geometric terms and its adaptation to the problem of assigning the input signal to a certain cluster. A neuron is considered to be a universal network element capable of performing orthogonal transformations, filtering, and other transformations of the input sequence. The layer of neurons is considered as an information converter with a certain kernel for solving the problems of orthogonal transformation, matched filtering, and nonlinear transformation for combining the spectra of the input influence of the network and its response. Based on the analysis of the proposed model, it is concluded that it is possible to reduce the number of neurons in the hidden layer and reduce the number of features for training the classifier 2020-06-19T13:30:20Z 2020-06-19T13:30:20Z 2020 Статья Vershkov, N.A., Kuchukov, V.A., Kuchukova, N.N., Babenko, M. The Wave Model of Artificial Neural Network // Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020. - 2020. - Номер статьи 9039172. - Pages 542-547 http://hdl.handle.net/20.500.12258/12084 en Proceedings of the 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, EIConRus 2020 application/pdf Institute of Electrical and Electronics Engineers Inc.
institution СКФУ
collection Репозиторий
language English
topic Artificial neural network
Correlation function
Spectral analysis
Data communication systems
spellingShingle Artificial neural network
Correlation function
Spectral analysis
Data communication systems
Vershkov, N. A.
Вершков, Н. А.
Kuchukov, V. A.
Кучуков, В. А.
Kuchukova, N. N.
Кучукова, Н. Н.
Babenko, M. G.
Бабенко, М. Г.
The wave model of artificial neural network
description The article deals with the modeling of artificial neural networks as a system of information transmission. The analysis of the existing theoretical approaches to the optimization of the structure and training of neural networks is carried out. The proposed model is based on the commonality of decoding processes in information transmission systems and clustering processes in neural networks. In the process of building a neuron model, we consider the well-known problem of determining the bandwidth capacity of the communication channel with noise in the geometric terms and its adaptation to the problem of assigning the input signal to a certain cluster. A neuron is considered to be a universal network element capable of performing orthogonal transformations, filtering, and other transformations of the input sequence. The layer of neurons is considered as an information converter with a certain kernel for solving the problems of orthogonal transformation, matched filtering, and nonlinear transformation for combining the spectra of the input influence of the network and its response. Based on the analysis of the proposed model, it is concluded that it is possible to reduce the number of neurons in the hidden layer and reduce the number of features for training the classifier
format Статья
author Vershkov, N. A.
Вершков, Н. А.
Kuchukov, V. A.
Кучуков, В. А.
Kuchukova, N. N.
Кучукова, Н. Н.
Babenko, M. G.
Бабенко, М. Г.
author_facet Vershkov, N. A.
Вершков, Н. А.
Kuchukov, V. A.
Кучуков, В. А.
Kuchukova, N. N.
Кучукова, Н. Н.
Babenko, M. G.
Бабенко, М. Г.
author_sort Vershkov, N. A.
title The wave model of artificial neural network
title_short The wave model of artificial neural network
title_full The wave model of artificial neural network
title_fullStr The wave model of artificial neural network
title_full_unstemmed The wave model of artificial neural network
title_sort wave model of artificial neural network
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2020
url https://dspace.ncfu.ru/handle/20.500.12258/12084
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