利用硅光子学处理神经形态信息

Active Photonic Platforms XI Pub Date : 2019-09-05 DOI:10.1117/12.2524707

P. Bienstman, J. Dambre, A. Katumba, Matthias Freiberger, Floris Laporte, A. Lugnan, Stijn Sackesyn, Chonghuai Ma

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引用次数: 1

摘要

本文介绍了基于储层计算等技术的硅光子学神经形态信息处理的最新成果。首先，我们讨论了如何使用被动储层计算在电信链路中执行非线性信号均衡。然后，我们介绍了一种训练方法，可以处理有限的重量分辨率的硬件实现的光子读出。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Neuromorphic information processing using silicon photonics

We present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. First, we dicuss how passive reservoir computing can be used to perform non-linear signal equalisation in telecom links. Then, we introduce a training method that can deal with limited weight resolution for a hardware implementation of a photonic readout.

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Active Photonic Platforms XI

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