2024-03-28T15:48:37Zhttp://digital.csic.es/dspace-oai/requestoai:digital.csic.es:10261/1171382021-12-28T15:46:01Zcom_10261_2855com_10261_4col_10261_2857
2015-06-25T09:12:06Z
urn:hdl:10261/117138
Parallel photonic information processing at gigabyte per second data rates using transient states
Brunner, Daniel
Soriano, Miguel C.
Mirasso, Claudio R.
Fischer, Ingo
Ministerio de Ciencia e Innovación (España)
European Commission
Govern de les Illes Balears
The increasing demands on information processing require novel computational concepts and true parallelism. Nevertheless, hardware realizations of unconventional computing approaches never exceeded a marginal existence. While the application of optics in super-computing receives reawakened interest, new concepts, partly neuro-inspired, are being considered and developed. Here we experimentally demonstrate the potential of a simple photonic architecture to process information at unprecedented data rates, implementing a learning-based approach. A semiconductor laser subject to delayed self-feedback and optical data injection is employed to solve computationally hard tasks. We demonstrate simultaneous spoken digit and speaker recognition and chaotic time-series prediction at data rates beyond 1 Gbyte/s. We identify all digits with very low classification errors and perform chaotic time-series prediction with 10% error. Our approach bridges the areas of photonic information processing, cognitive and information science. © 2013 Macmillan Publishers Limited. All rights reserved.
2015-06-25T09:12:06Z
2015-06-25T09:12:06Z
2013-01-15
2015-06-25T09:12:06Z
artículo
Nature Communications 4: 1364 (2013)
http://hdl.handle.net/10261/117138
10.1038/ncomms2368
http://dx.doi.org/10.13039/501100004837
http://dx.doi.org/10.13039/501100000780
23322052
eng
Publisher's version
http://dx.doi.org/10.1038/ncomms2368
Sí
http://creativecommons.org/licenses/by-nc-sa/3.0/
openAccess
Nature Publishing Group