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Photonic Extreme Learning Machine based on Frequency Multiplexing

par Lupo, Alessandro ;Butschek, Lorenz ;Massar, Serge
Référence Optics express, 29, page (28257-28276)
Publication Publié, 2021-08-17

Article révisé par les pairs

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Résumé :

The optical domain is a promising field for the physical implementation of neural networks, due to the speed and parallelism of optics. Extreme learning machines (ELMs) are feed-forward neural networks in which only output weights are trained, while internal connections are randomly selected and left untrained. Here we report on a photonic ELM based on a frequency-multiplexed fiber setup. Multiplication by output weights can be performed either offline on a computer or optically by a programmable spectral filter. We present both numerical simulations and experimental results on classification tasks and a nonlinear channel equalization task.