Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing
Photonic information processing beyond Turing: an optoelectronic implementation of reservoir computing
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DOI：
10.1364/oe.20.003241
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发表时间：
2012-01-30
期刊：
影响因子：
3.8
通讯作者：
Fischer, I.
中科院分区：
文献类型：
--
作者：
Larger, L.;Soriano, M. C.;Fischer, I.
许多信息处理的挑战是难以解决与传统的图灵或冯诺依曼的方法。因此，实施非常规的计算方法是必不可少的，光学提供了有前途的机会。在这里，我们实验演示了光学信息处理使用非线性光电振荡器受到延迟反馈。我们实现了一个神经启发的概念，称为水库计算，被证明具有通用的计算能力。我们特别利用一个复杂的动态系统的输入数据流的瞬态响应。我们采用口语数字识别和时间序列预测任务作为基准，实现有竞争力的处理数字的优点。(C)2012美国光学学会
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