Photonic Reservoir Computing with Coupled Semiconductor Optical Amplifiers

We propose photonic reservoir computing as a new approach to optical signal processing and it can be used to handle for example large scale pattern recognition. Reservoir computing is a new learning method from the field of machine learning. This has already led to impressive results in software but...

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Bibliographic Details
Published inOptical SuperComputing pp. 46 - 55
Main Authors Vandoorne, Kristof, Dierckx, Wouter, Schrauwen, Benjamin, Verstraeten, David, Bienstman, Peter, Baets, Roel, Van Campenhout, Jan
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Echo State Network
Recurrent Neural Network
Reservoir Computing
Spectral Radius
Triangular Waveform
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Summary:We propose photonic reservoir computing as a new approach to optical signal processing and it can be used to handle for example large scale pattern recognition. Reservoir computing is a new learning method from the field of machine learning. This has already led to impressive results in software but integrated photonics with its large bandwidth and fast nonlinear effects would be a high-performance hardware platform. Therefore we developed a simulation model which employs a network of coupled Semiconductor Optical Amplifiers (SOA) as a reservoir. We show that this kind of photonic reservoir performs even better than classical reservoirs on a benchmark classification task.
ISBN:3540856722
9783540856726
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-85673-3_4