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Authors: K.T Vandoorne, D. Verstraeten, B. Schrauwen, J. Dambre, P. Bienstman
Title: Delays in photonic reservoir computing with semiconductor optical amplifiers
Format: International Conference Proceedings
Publication date: 12/2011
Journal/Conference/Book: IEEE Photonics Benelux Chapter Annual Symposium
Location: Ghent, Belgium
Citations: Look up on Google Scholar
Download: Download this Publication (628KB) (628KB)


Reservoir computing is a decade old framework from the field of machine learning to use
and train recurrent neural networks and it splits the network in a reservoir that does the
‘computation’ and a simple readout function. This technique has been among the stateof-
the-art for many classification problems. So far implementations have been mainly
software based, but a hardware implementation offers the promise of being low-power
and fast. We will show that photonic reservoirs can achieve an excellent performance on
a benchmark isolated digit recognition task, if the interconnection delay is optimized and
the phase controlled. Furthermore we will show that this optimal delay is dependent on
the input speed of the audio signal.

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