Design and spectral reconstruction assisted by intelligent algorithms for high-resolution Fourier transform spectrometer

Huaijian Luo, Zhuili Huang, Chuang Xu, Alan Pak Tao Lau, Changyuan Yu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

A miniature Fourier transform spectrometer is designed with tailored optical path differences for visible spectral reconstruction. The combination of intelligent algorithms, the convex optimization algorithm (CVX) and the one-dimension modified convolutional neural network (Unet), is used to retrieve spectra under measurement with noise. This scheme recovers four kinds of spectra accurately with the mean-square error of 8.32 × 10-4.

Original languageEnglish
Title of host publication30th Wireless and Optical Communications Conference, WOCC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages153-156
Number of pages4
ISBN (Electronic)9781665427722
DOIs
Publication statusPublished - Oct 2021
Event30th Wireless and Optical Communications Conference, WOCC 2021 - Taipei, Taiwan
Duration: 7 Oct 20218 Oct 2021

Publication series

Name2021 30th Wireless and Optical Communications Conference, WOCC 2021

Conference

Conference30th Wireless and Optical Communications Conference, WOCC 2021
Country/TerritoryTaiwan
CityTaipei
Period7/10/218/10/21

Keywords

  • Fourier transform spectrometer
  • High resolution
  • Intelligent algorithm
  • Mach-Zehnder interferometer
  • Spectroscopy

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Computer Networks and Communications
  • Signal Processing

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