Neurocomputer architecture based on spiking neural network and its optoelectronic implementation

被引:0
作者
Kolesnytskyj, Oleh K. [1 ]
Kutsman, Vladislav V. [1 ]
Skorupski, Krzysztof [2 ]
Arshidinova, Mukaddas [3 ]
机构
[1] Vinnytsia Natl Tech Univ, Khmelnytske Hwy 95, UA-21000 Vinnytsia, Vinnytska Oblas, Ukraine
[2] Lublin Univ Technol, Nadbystrzycka 38A, PL-20618 Lublin, Poland
[3] Al Farabi Kazakh Natl Univ, Alma Ata 050040, Kazakhstan
来源
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS 2019 | 2019年 / 11176卷
关键词
neurocomputer; neurocomputer architecture; spiking neural network; construction principles; hardware implementation; SYSTEM;
D O I
10.1117/12.2536607
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
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.
引用
收藏
页数:9
相关论文
共 29 条
[11]   Method of magneto-elastic control of mechanic rigidity in assemblies of hydropower units [J].
Kukharchuk, Vasyl V. ;
Bogachuk, Volodymyr V. ;
Hraniak, Valerii F. ;
Wojcik, Waldemar ;
Suleimenov, Batyrbek ;
Karnakova, Gaini .
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH ENERGY PHYSICS EXPERIMENTS 2017, 2017, 10445
[12]  
Kvyetnyy R. N., 2016, P SOC PHOTO-OPT INS, V10031
[13]   Improving the quality perception of digital images using modified method of the eye aberration correction [J].
Kvyetnyy, Roman ;
Sofina, Olga ;
Orlyk, Pavel ;
Utreras, Andres J. ;
Smolarz, Andrzej ;
Wojcik, Waldemar ;
Orazalieva, Sandugash .
PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS 2016, 2016, 10031
[14]   Blur recognition using second fundamental form of image surface [J].
Kvyetnyy, Roman ;
Bunyak, Yuriy ;
Sofina, Olga ;
Kotyra, Andrzej ;
Romaniuk, Ryszard S. ;
Tuleshova, Azhar .
OPTICAL FIBERS AND THEIR APPLICATIONS 2015, 2015, 9816
[15]  
Maass W., 2001, PULSED NEURAL NETWOR, P377
[16]  
Mirkes E. M., 1998, NEYROCOMPUTER
[17]  
Natschlager T., 2002, Telematik, V8, P39
[18]   Fibre Bragg Gratings written in highly birefringent microstructured fiber as very sensitive strain sensors [J].
Tenderenda, T. ;
Murawski, M. ;
Szymanski, M. ;
Becker, M. ;
Rothhardt, M. ;
Bartelt, H. ;
Mergo, P. ;
Poturaj, K. ;
Makara, M. ;
Skorupski, K. ;
Marc, P. ;
Jaroszewicz, L. R. ;
Nasilowski, T. .
MICRO-STRUCTURED AND SPECIALTY OPTICAL FIBRES, 2012, 8426
[19]  
Vassilenko S., 2016, P 10 INT SCI PRACT C, P149
[20]  
von Neumann J., 1951, CEREBRAL MECH BEHAV, P1, DOI DOI 10.1126/SCIENCE.115.2990.440