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Title: Neural network decoder of automatic process control system
Authors: Koldaev, A. I.
Колдаев, А. И.
Boldyrev, D. V.
Болдырев, Д. В.
Evdokimov, A. A.
Евдокимов, А. А.
Keywords: Controllers;Residue number system (RNS);Neural networks;Automation;Control systems;Data transfer;Error correction;Process control;Table lookup;Numbering systems
Issue Date: 2019
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Koldaev, A.I., Boldyrev, D.V., Evdokimov, A.A. Neural Network Decoder of Automatic Process Control System // 2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019. - 2019. - Номер статьи 8934411
Series/Report no.: 2019 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2019
Abstract: In this paper the new associative neural network calculating Lee code distance which allows defining in real time the closest pattern in residue number system is considered. The presented neural network allows to detect and correct the errors in data transfer in automatic control systems with high error rate. The neural network able to form the limited list of the most probable sets of residues from legitimate range of residue number system representation in case of insufficient redundancy for error correction. Designed neural network consist of simple modulo adders and lookup tables, and is able to convert data stream from residue number system to positional number system with error correct
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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