Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12258/7117
Title: Adaptive finite ring neural network
Authors: Evdokimov, A. A.
Евдокимов, А. А.
Keywords: Finite ring neural network;Modular reduction;Training algorithm
Issue Date: 2018
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Evdokimov, A., Afonin, M. Adaptive finite ring neural network // IEEE 12th International Conference on Application of Information and Communication Technologies, AICT 2018 - Proceedings. - 2018. - Article number 8747166
Series/Report no.: IEEE 12th International Conference on Application of Information and Communication Technologies, AICT 2018 - Proceedings
Abstract: A new neural network structure of the modular reduction are presented. The new structure is oriented to learning by examples: the number of layers is fixed for any module, the slow approach to the resulting value is excluded, the result is the remainder modulo and does not require an adjustment. Developed three training algorithm of finite ring neural network: training sample inputs and desired outputs, training only on the desired output and training only for the sampling of input signals. The developed algorithms allow to adapt the finite ring neural network to the new module and, unlike the known solutions, do not require changing the network architecture
URI: https://www.scopus.com/record/display.uri?eid=2-s2.0-85070215972&origin=resultslist&sort=plf-f&src=s&st1=Adaptive+finite+ring+neural+network&st2=&sid=00517e04cd9db0cd4826521d40659860&sot=b&sdt=b&sl=50&s=TITLE-ABS-KEY%28Adaptive+finite+ring+neural+network%29&relpos=0&citeCnt=0&searchTerm=
http://hdl.handle.net/20.500.12258/7117
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