Wavefront Restoration Technology of Dynamic Non-Uniform Intensity Distribution Based on Extreme Learning Machine
Non-uniform intensity distribution of laser near-field beam results in the irregular shape of the spot in the wavefront sensor. The intensity of some sub-aperture spots may be too weak to be detected, and the accuracy of wavefront restoration is seriously affected. Therefore, an extreme learning machine method is proposed to realize high precision wavefront restoration under dynamic non-uniform intensity distribution. The simulation results show that this method has better accuracy of wavefront restoration than the classical modal algorithm under dynamic non-uniform intensity distribution. The root mean square error of the residual wavefront for the proposed method is only 2.9% of the initial value.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2021 |
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Erschienen: |
2021 |
Enthalten in: |
Zur Gesamtaufnahme - volume:21 |
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Enthalten in: |
Sensors (Basel, Switzerland) - 21(2021), 11 vom: 04. Juni |
Sprache: |
Englisch |
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Beteiligte Personen: |
Lin, Haiqi [VerfasserIn] |
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Links: |
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Themen: |
Journal Article |
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Anmerkungen: |
Date Revised 02.04.2024 published: Electronic Citation Status PubMed-not-MEDLINE |
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doi: |
10.3390/s21113877 |
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funding: |
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Förderinstitution / Projekttitel: |
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PPN (Katalog-ID): |
NLM327465069 |
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520 | |a Non-uniform intensity distribution of laser near-field beam results in the irregular shape of the spot in the wavefront sensor. The intensity of some sub-aperture spots may be too weak to be detected, and the accuracy of wavefront restoration is seriously affected. Therefore, an extreme learning machine method is proposed to realize high precision wavefront restoration under dynamic non-uniform intensity distribution. The simulation results show that this method has better accuracy of wavefront restoration than the classical modal algorithm under dynamic non-uniform intensity distribution. The root mean square error of the residual wavefront for the proposed method is only 2.9% of the initial value | ||
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700 | 1 | |a Wang, Shuai |e verfasserin |4 aut | |
700 | 1 | |a Yang, Ping |e verfasserin |4 aut | |
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