arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2008.11247physics.opticscs.NE
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基于频率复用的光子油藏计算机

Photonic reservoir computer based on frequency multiplexing

Lorenz Butschek, Akram Akrout, Evangelia Dimitriadou, Alessandro Lupo, Marc Haelterman, Serge Massar

摘要:

水库计算是一种大脑启发的信息处理方法,非常适合模拟实现。我们报告了一个光子实现的水库计算机,利用频域复用编码神经元状态。该系统以20 MHz的速率同时处理25条梳状线(即25个神经元)。我们说明了两个标准的基准任务的性能:信道均衡和时间序列预测。我们还表明,频率复用允许输出权重在光域中实现,通过光衰减。我们讨论了高速高性能低足迹实现的前景。

英文摘要:

Reservoir computing is a brain inspired approach for information processing, well suited to analogue implementations. We report a photonic implementation of a reservoir computer that exploits frequency domain multiplexing to encode neuron states. The system processes 25 comb lines simultaneously (i.e. 25 neurons), at a rate of 20 MHz. We illustrate performances on two standard benchmark tasks: channel equalization and time series forecasting. We also demonstrate that frequency multiplexing allows output weights to be implemented in the optical domain, through optical attenuation. We discuss the perspectives for high speed high performance low footprint implementations.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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