Publication:
Memristive element functional model for computer based analysis and hardware emulation of pulsed neurons adaptive networks

Дата
2019
Авторы
Alyushin, S.
Arkhangelsky, V.
Alyushin, A.
Journal Title
Journal ISSN
Volume Title
Издатель
Научные группы
Организационные подразделения
Организационная единица
Институт лазерных и плазменных технологий
Стратегическая цель Института ЛаПлаз – стать ведущей научной школой и ядром развития инноваций по лазерным, плазменным, радиационным и ускорительным технологиям, с уникальными образовательными программами, востребованными на российском и мировом рынке образовательных услуг.
Выпуск журнала
Аннотация
© 2019 IEEE The development of efficient and invariant to the integrated technology models for rapid design and behavioral analysis of new neural-like information processing systems of large dimensions is of particular significance. A special role in this process is played by functional models of memristive elements with computationally efficient implementation in modern CAD systems based on a limited number of library functional and electronic components (resistors - R, capacitors - C, active components such as OPAs, MOS structures and the like) and allowing simple hardware emulation. This paper presents a schematic model and an extended mathematical description of the functional memristor element with the structure 1C1R1MOS, proposed by the authors earlier. Now we describe its main electrical characteristics and operating modes. We also present the experimental study results of the memristor functional model in its hardware emulation as part of an artificial neural network.
Описание
Ключевые слова
Цитирование
Alyushin, S. Memristive element functional model for computer based analysis and hardware emulation of pulsed neurons adaptive networks / Alyushin, S., Arkhangelsky, V., Alyushin, A. // Proceedings of the 2019 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2019. - 2019. - P. 2072-2078. - 10.1109/EIConRus.2019.8657113
Коллекции