神经形态工程学
光子学
信号处理
计算机科学
激光器
互连
Spike(软件开发)
电子工程
物理
电信
光电子学
人工神经网络
工程类
人工智能
光学
软件工程
雷达
作者
Paul R. Prucnal,Bhavin J. Shastri,Thomas Ferreira de Lima,Mitchell A. Nahmias,Alexander N. Tait
出处
期刊:Advances in Optics and Photonics
[The Optical Society]
日期:2016-05-20
卷期号:8 (2): 228-228
被引量:221
摘要
Recently, there has been tremendous interest in excitable optoelectronic devices and in particular excitable semiconductor lasers that could potentially enable unconventional processing approaches beyond conventional binary-logic-based approaches. In parallel, there has been renewed investigation of non-von Neumann architectures driven in part by incipient limitations in aspects of Moore's law. These neuromorphic architectures attempt to decentralize processing by interweaving interconnection with computing while simultaneously incorporating time-resolved dynamics, loosely classified as spiking (a.k.a. excitability). The rapid and efficient advances in CMOS-compatible photonic interconnect technologies have led to opportunities in optics and photonics for unconventional circuits and systems. Effort in the budding research field of photonic spike processing aims to synergistically integrate the underlying physics of photonics with bio-inspired processing. Lasers operating in the excitable regime are dynamically analogous with the spiking dynamics observed in neuron biophysics but roughly 8 orders of magnitude faster. The field is reaching a critical juncture at which there is a shift from studying single devices to studying an interconnected network of lasers. In this paper, we review the recent research in the information processing abilities of such lasers, dubbed "photonic neurons," "laser neurons," or "optical neurons." An integrated network of such lasers on a chip could potentially grant the capacity for complex, ultrafast categorization and decision making to provide a range of computing and signal processing applications, such as sensing and manipulating the radio frequency spectrum and for hypersonic aircraft control.
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