Photonic Enabled Neural Network: Key Components, Heterogeneous Architecture and Intelligent Applications
A special issue of Photonics (ISSN 2304-6732).
Deadline for manuscript submissions: closed (15 February 2022) | Viewed by 4192
Special Issue Editors
Interests: Intelligent Microwave Lightwave Integration (iMLic)
Interests: all-optical signal processing; optical engineering; fiber optics; guided wave optics
Special Issues, Collections and Topics in MDPI journals
Interests: short reach optical interconnects and networking; ultra-high density and programmable optical chip; optical neural network
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The development of novel computing hardware and architecture is of great strategic and economic significance to the leap-forward progress of artificial intelligence technology in the post-Moore era, and photonic enabled neural networks have become the disruptive path for future computing architecture due to their huge advantages in terms of processing speed and power consumption. In recent years, various integrated photonic neural networks, based on MZIs or microring resonators, have been proposed to accelerate the matrix operations. In addition, photonic computing architecture including convolutional neural networks, recurrent neural networks, and programmable reservoir computing systems are riding the wave of implementing large-scale intelligent applications such as vision, voice, and natural language classification. The purpose of this Special Issue is to highlight the progress in photonic-enabled neural networks, including key components, heterogeneous architectures, and intelligent applications. We believe that photonic involvement will foster new technologies for disruptive computing devices and architecture.
Prof. Dr. Weiwen Zou
Prof. Dr. Zhi Wang
Dr. Wenjia Zhang
Guest Editors
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Keywords
- optical neural network
- optical convolutional neural network
- optical recurrent neural network
- programmable photonics
- optical unitary conversion
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