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Applied Sciences
Special Issues
Recent Advances in Microwave Photonics
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Recent Advances in Microwave Photonics

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: 20 May 2024 | Viewed by 2339

Special Issue Editors

Dr. Nuannuan Shi

E-Mail Website
Guest Editor
Institute of Semiconductors Chinese Academy of Sciences, Beijing, China
Interests: microwave photonics; integrated microwave photonics; signal processing and photonics AI
Dr. Tengfei Hao

E-Mail Website
Guest Editor
Institute of Semiconductors Chinese Academy of Sciencesdisabled, Beijing, China
Interests: microwave photonics; integrated microwave photonics; optoelectronic oscillator

Special Issue Information

Dear Colleagues,

We are inviting submissions to this Special Issue on Recent Advances in Microwave Photonics.

Microwave photonics is an interdisciplinary field that integrates optics and radiofrequency (RF) engineering and has attracted substantial interest in recent years, advancing many applications in defense, communication networks, imaging, and instrumentations. Microwave photonics uses optical devices and technologies to generate, process, manipulate, and distribute RF signals, enabling functions or performances that are complex or not achievable through the use of traditional RF systems. Microwave photonics has attracted substantial interest from both academia and industry, and an array of new insights and breakthroughs have been proposed and demonstrated in recent years.

This Special Issue will be dedicated to recent advances in the prosperous field of microwave photonics. Topics of interest include (but are not limited to):

  • Microwave photonic signal generation;
  • Microwave photonic signal processing;
  • Microwave photonic radar;
  • True time delay beamforming ;
  • Integrated microwave photonics;
  • Applications of microwave photonics.

Dr. Nuannuan Shi
Dr. Tengfei Hao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microwave photonics
  • integrated microwave photonics
  • microwave photonic link
  • microwave photonic signal processor
  • optoelectronic oscillator
  • radio over fiber

Published Papers (1 paper)

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Review

19 pages, 4980 KiB  
Review
Optical Convolutional Neural Networks: Methodology and Advances (Invited)
by Xiangyan Meng, Nuannuan Shi, Guangyi Li, Wei Li, Ninghua Zhu and Ming Li
Appl. Sci. 2023, 13(13), 7523; https://doi.org/10.3390/app13137523 - 26 Jun 2023
Cited by 2 | Viewed by 1979
Abstract
As a leading branch of deep learning, the convolutional neural network (CNN) is inspired by the natural visual perceptron mechanism of living things, showing great application in image recognition, language processing, and other fields. Photonics technology provides a new route for intelligent signal [...] Read more.
As a leading branch of deep learning, the convolutional neural network (CNN) is inspired by the natural visual perceptron mechanism of living things, showing great application in image recognition, language processing, and other fields. Photonics technology provides a new route for intelligent signal processing with the dramatic potential of its ultralarge bandwidth and ultralow power consumption, which automatically completes the computing process after the signal propagates through the processor with an analog computing architecture. In this paper, we focus on the key enabling technology of optical CNN, including reviewing the recent advances in the research hotspots, overviewing the current challenges and limitations that need to be further overcome, and discussing its potential application. Full article
(This article belongs to the Special Issue Recent Advances in Microwave Photonics)
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