Computer Science > Emerging Technologies
arXiv:2401.14371 (cs)
[Submitted on 25 Jan 2024]
Title:Efficient Optimisation of Physical Reservoir Computers using only a Delayed Input
View a PDF of the paper titled Efficient Optimisation of Physical Reservoir Computers using only a Delayed Input, by Enrico Picco and 2 other authors
View PDFAbstract:We present an experimental validation of a recently proposed optimization technique for reservoir computing, using an optoelectronic setup. Reservoir computing is a robust framework for signal processing applications, and the development of efficient optimization approaches remains a key challenge. The technique we address leverages solely a delayed version of the input signal to identify the optimal operational region of the reservoir, simplifying the traditionally time-consuming task of hyperparameter tuning. We verify the effectiveness of this approach on different benchmark tasks and reservoir operating conditions.
| Subjects: | Emerging Technologies (cs.ET); Artificial Intelligence (cs.AI); Neural and Evolutionary Computing (cs.NE); Optics (physics.optics) |
| Cite as: | arXiv:2401.14371 [cs.ET] |
| (orarXiv:2401.14371v1 [cs.ET] for this version) | |
| https://doi.org/10.48550/arXiv.2401.14371 arXiv-issued DOI via DataCite |
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View a PDF of the paper titled Efficient Optimisation of Physical Reservoir Computers using only a Delayed Input, by Enrico Picco and 2 other authors
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