Ultrafast neuromorphic photonic image processing with a VCSEL neuron.

Ultrafast neuromorphic photonic image processing with a VCSEL neuron.
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DOI:
10.1038/s41598-022-08703-1
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发表时间:
2022-03-22
期刊:
影响因子:
4.6
通讯作者:
Hurtado A
Hurtado A
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Robertson J;Kirkland P;Alanis JA;Hejda M;Bueno J;Di Caterina G;Hurtado A

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对人工智能(AI)系统的需求不断增长,这凸显了对新的AI优化硬件的重大需求。神经形态(类脑)处理器是一个非常有前途的解决方案,光子实现越来越受到关注。其中,基于垂直腔面发射激光器(VCSEL)的方法由于其有利的属性和成熟的技术而引起了人们的兴趣。在这里,我们展示了一个硬件友好的神经形态光子尖峰处理器,使用一个VCSEL,全光学图像边缘特征检测。这利用了基于VCSEL的光子神经元以高速整合时间编码的像素数据的能力;并在检测到所需的图像特征时发出快速(100 ps长)的光学尖峰。此外,光子系统与软件实现的尖峰神经网络相结合,为复杂的图像分类任务提供了完整的平台。因此,这项工作突出了基于VCSEL的平台的潜力,用于与当前计算和通信系统连接的新型超快全光学神经形态处理器,用于未来的光激活AI和计算机视觉功能。
The ever-increasing demand for artificial intelligence (AI) systems is underlining a significant requirement for new, AI-optimised hardware. Neuromorphic (brain-like) processors are one highly-promising solution, with photonic-enabled realizations receiving increasing attention. Among these, approaches based upon vertical cavity surface emitting lasers (VCSELs) are attracting interest given their favourable attributes and mature technology. Here, we demonstrate a hardware-friendly neuromorphic photonic spike processor, using a single VCSEL, for all-optical image edge-feature detection. This exploits the ability of a VCSEL-based photonic neuron to integrate temporally-encoded pixel data at high speed; and fire fast (100 ps-long) optical spikes upon detecting desired image features. Furthermore, the photonic system is combined with a software-implemented spiking neural network yielding a full platform for complex image classification tasks. This work therefore highlights the potential of VCSEL-based platforms for novel, ultrafast, all-optical neuromorphic processors interfacing with current computation and communication systems for use in future light-enabled AI and computer vision functionalities.
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