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Proceedings Paper

Neurocomputer architecture based on spiking neural network and its optoelectronic implementation
Author(s): Oleh K. Kolesnytskyj; Vladislav V. Kutsman; Krzysztof Skorupski; Mukaddas Arshidinova
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Paper Abstract

The paper clarifies neurocomputer and neurocomputer architecture term definitions. The choice of spiking neural network as neurocomputer operating unit is substantiated. The spiking neurocomputer organization principles are formulated by analyzing and generalization of the current level of knowledge on neurocomputer architecture (based on analogy with the well-known von Neumann digital computer organization principles). Analytical overview of current projects on spiking neural networks hardware implementation is conducted. Their major disadvantages are highlighted. Optoelectronic hardware implementation of spiking neural network is proposed as such that is free of mentioned disadvantages due to usage of optical signals for communication between neurons, as well as organization of learning through hardware. The main technical parameters of the proposed spiking neural network are estimated.

Paper Details

Date Published: 6 November 2019
PDF: 9 pages
Proc. SPIE 11176, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019, 1117609 (6 November 2019); doi: 10.1117/12.2536607
Show Author Affiliations
Oleh K. Kolesnytskyj, Vinnytsia National Technical Univ. (Ukraine)
Vladislav V. Kutsman, Vinnytsia National Technical Univ. (Ukraine)
Krzysztof Skorupski, Lublin Univ. of Technology (Poland)
Mukaddas Arshidinova, Al-Farabi Kazakh National Univ. (Kazakhstan)

Published in SPIE Proceedings Vol. 11176:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2019
Ryszard S. Romaniuk; Maciej Linczuk, Editor(s)

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