| Issue |
EPJ Web Conf.
Volume 287, 2023
EOS Annual Meeting (EOSAM 2023)
|
|
|---|---|---|
| Article Number | 13006 | |
| Number of page(s) | 2 | |
| Section | Focused Sessions (FS) 4- Machine Learning and Photonic Artificial Intelligence / Optical Neural Networks and Neuromorphic Computing | |
| DOI | https://doi.org/10.1051/epjconf/202328713006 | |
| Published online | 18 October 2023 | |
https://doi.org/10.1051/epjconf/202328713006
Computation and implementation of large scalable Spiking Neural Network
1 Institute Femto-ST, Université Franche-Comté, CNRS UMR6174, Besançon, France
2 Institute of Photonics, Department of Physics, University of Strathclyde, Glasgow G1 1RD, UK
* Corresponding author: ria.talukder@femto-st.fr
Published online: 18 October 2023
Photonic neural networks are a highly sought-after area of research due to their potential for high-performance complex computing. Unlike artificial neural networks, which use simple nonlinear maps, biological neurons transmit information and perform computations through spikes that depend on spike time and/or rate. Through comprehensive studies and experiments, a strong foundation has been laid for the development of photonic neural networks. We have recently developed a large-scale spiking neural network, which serves as a proof-of-concept experiment for novel bio-inspired learning concepts. This breakthrough is significant because it demonstrates the potential of using photonic neural networks for advanced computing and highlights the importance of incorporating biological principles into artificial intelligence research.
© The Authors, published by EDP Sciences, 2023
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