Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing

被引:646
作者
Larger, L. [1 ]
Soriano, M. C. [2 ]
Brunner, D. [2 ]
Appeltant, L. [3 ]
Gutierrez, J. M. [4 ]
Pesquera, L. [4 ]
Mirasso, C. R. [2 ]
Fischer, I. [2 ]
机构
[1] Univ Franche Comte, Dept Opt, UMR CNRS FEMTO ST 6174, F-25030 Besancon, France
[2] UIB CSIC, IFISC, E-07122 Palma De Mallorca, Spain
[3] Vrije Univ Brussel, Appl Phys Res Grp APHY, B-1050 Brussels, Belgium
[4] IFCA UNICAN CSIC, Inst Fis Cantabria, E-39005 Santander, Spain
关键词
DYNAMICS; SYSTEM; STATE; NETWORKS; DEVICES; OPTICS; CHAOS;
D O I
10.1364/OE.20.003241
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Many information processing challenges are difficult to solve with traditional Turing or von Neumann approaches. Implementing unconventional computational methods is therefore essential and optics provides promising opportunities. Here we experimentally demonstrate optical information processing using a nonlinear optoelectronic oscillator subject to delayed feedback. We implement a neuro-inspired concept, called Reservoir Computing, proven to possess universal computational capabilities. We particularly exploit the transient response of a complex dynamical system to an input data stream. We employ spoken digit recognition and time series prediction tasks as benchmarks, achieving competitive processing figures of merit. (C) 2012 Optical Society of America
引用
收藏
页码:3241 / 3249
页数:9
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