Neurocomputer architecture based on spiking neural network and its optoelectronic implementation
Fragment książki (Rozdział monografii pokonferencyjnej)
MNiSW
20
Poziom I
| Status: | |
| Autorzy: | Kolesnytskyj Oleh K., Kutsman Vladislav V., Skorupski Krzysztof, Arshidinova Mukaddas |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Strony: | 60 - 68 |
| Web of Science® Times Cited: | 0 |
| Scopus® Cytowania: | 1 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | TAK |
| Nazwa konferencji: | XLIV-th IEEE-SPIE Joint Symposium on Photonics, Web Engineering, Electronics for Astronomy and High Energy Physics Experiments |
| Skrócona nazwa konferencji: | XLIV SPIE-IEEE-PSP 2019 |
| URL serii konferencji: | LINK |
| Termin konferencji: | 26 maja 2019 do 2 czerwca 2019 |
| Miasto konferencji: | Wilga |
| Państwo konferencji: | POLSKA |
| Publikacja OA: | NIE |
| Abstrakty: | angielski |
| 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. |
