Journal of Siberian Federal University. Engineering & Technologies: The Realization of Artificial Neural Networks in Nonpositional Value for Automated Control Systems

Journal of Siberian Federal University. Engineering & Technologies / The Realization of Artificial Neural Networks in Nonpositional Value for Automated Control Systems

Issue: Journal of Siberian Federal University. Engineering & Technologies. 2018 11 (1)
Authors: Vasetsky, Viktor V.
Contact information: Васецкий, В.В.: Военный учебно-научный центр Военно-воздушных сил «Военно-воздушная академия имени профессора Н.Е. Жуковского и Ю.А. Гагарина» Россия, 394064, Воронеж, ул. Старых Большевиков, 54а; Vasetsky, Viktor V.:Military Education and Research Centre of Military-Air Forces «Military-Air Academy Named After Professor N.E. Zhukovsky and Yu.A. Gagarin» 54а Starykh Bolshevikov Str., Voronezh, 394064, Russia;
Keywords: Nonpositional number system; the system of residual classes; artificial neuron; failover neurocomputer
Abstract: This article raises the problem of using nonpositional number systems, in particular the system of residual classes, which is a parallel system and provides a level parallelism execution of elementary operations in automated control systems
Pages: 43-47
Paper at repository of SibFU: https://elib.sfu-kras.ru/handle/2311/70393