Contemporary implementations of spiking bio-inspired neural networks

Schegolev, A.E.; Bastrakova, M.V.; Sergeev, M.A.; Maksimovskaya, A.A.; Klenov, N.V.; Soloviev, I.I.

Авторы: Schegolev Andrey E., Bastrakova Marina V., Sergeev Michael A., Maksimovskaya Anastasia A., Klenov Nikolay V., Soloviev Igor I.
Журнал: Mesoscience & Nanotechnology
Том: 1
Номер: 1
Год издания: 2024
Издательство: MIPT Centre for advanced mesoscience and nanotechnology
Местоположение издательства: Москва
Первая страница: 01
Последняя страница: 01005
Аннотация: The extensive development of the field of spiking neural networks has led to many areas of research that have a direct impact on people’s lives. As the most bio-similar of all neural networks, spiking neural networks not only allow for the solution of recognition and clustering problems (including dynamics), but they also contribute to the growing understanding of the human nervous system. Our analysis has shown that hardware implementation is of great importance, since the specifics of the physical processes in the network cells affect their ability to simulate the neural activity of living neural tissue, the efficiency of certain stages of information processing, storage and transmission. This survey reviews existing hardware neuromorphic implementations of bio-inspired spiking networks in the ”semiconductor”, ”superconductor”, and ”optical” domains. Special attention is given to the potentials for effective ”hybrids” of different approaches.
Добавил в систему: Щеголев Андрей Евгеньевич

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Contemporary implementations of spiking bio-inspired neural networksстатья

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