Photonic Blind Source Separation Based on Point cloud Analysis and Deep Learning

Taichu Shi; James Garofolo; Yang Qi; Ben Wu

doi:10.1364/FIO.2023.FD4.3

Frontiers in Optics + Laser Science 2023 (FiO, LS)
Technical Digest Series (Optica Publishing Group, 2023),
paper FD4.3
•https://doi.org/10.1364/FIO.2023.FD4.3

Photonic Blind Source Separation Based on Point cloud Analysis and Deep Learning

Taichu Shi, James Garofolo, Yang Qi, and Ben Wu

Frontiers in Optics 2023

Tacoma, Washington United States
9–12 October 2023
ISBN: 978-1-957171-29-6

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T. Shi, J. Garofolo, Y. Qi, and B. Wu, "Photonic Blind Source Separation Based on Point cloud Analysis and Deep Learning," in Frontiers in Optics + Laser Science 2023 (FiO, LS), Technical Digest Series (Optica Publishing Group, 2023), paper FD4.3.

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Abstract

We proposed and demonstrated a blind source separation method utilizing deep learning-based point cloud analysis algorithms. By treating the signals as point clouds and utilizing their statistical information, signal of interest can be recovered.

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