| Issue |
EPJ Web Conf.
Volume 287, 2023
EOS Annual Meeting (EOSAM 2023)
|
|
|---|---|---|
| Article Number | 13010 | |
| 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/202328713010 | |
| Published online | 18 October 2023 | |
https://doi.org/10.1051/epjconf/202328713010
Experimental Investigation of Time-Stretch-Based Reservoir Computing with an Optical Input Mask
1 School of Engineering, University of Kent, Canterbury CT2 7NT, United Kingdom.
2 School of Automation, Guangdong University of Technology, Guangzhou, China.
* Corresponding author: C.Wang@kent.ac.uk
Published online: 18 October 2023
In this paper, we experimentally demonstrated a novel all-optical reservoir computer with an all optical input mask. The combination of the binary random masks and the time-stretched ultrashort pulses has increased the system’s classification performance. Compared with the traditional digital masks, this method shows superior classification performance in spoken-digit classification tasks and eliminates the need for high-speed modulation for digital masks.
© The Authors, published by EDP Sciences, 2023
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