Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/106917
| Title: | Principle component analysis and random forest based all-fiber activity monitoring | Authors: | Han, S Xu, W You, S Dong, B Yu, C Zhao, W |
Issue Date: | 2019 | Source: | Asia Communications and Photonics Conference (ACPC) 2019, OSA Technical Digest (Optica Publishing Group, 2019), paper S4G.4 | Abstract: | An activity monitoring algorithm based on principle component analysis and random forest is proposed, identifying three kinds of activities obtained from Mach-Zehnder interferometer with accuracy of 99.5% within one second, namely, normal, nobody and movement. | Publisher: | Optica Publishing Group | ISBN: | 978-1-943580-70-5 | Description: | Asia Communications and Photonics Conference 2019, Chengdu China, 2-5 November 2019 | Rights: | © 2019 The Author(s) The following publication S. Han, W. Xu, S. You, B. Dong, C. Yu, and W. Zhao, "Principle Component Analysis and Random Forest Based All-Fiber Activity Monitoring," in Asia Communications and Photonics Conference (ACPC) 2019, OSA Technical Digest (Optica Publishing Group, 2019), paper S4G.4 is available at https://opg.optica.org/abstract.cfm?uri=acpc-2019-S4G.4&origin=search. |
| Appears in Collections: | Conference Paper |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| acpc-2019-s4g.4.pdf | 613.41 kB | Adobe PDF | View/Open |
Access
View full-text via PolyU eLinks 
Page views
181
Citations as of Nov 10, 2025
Downloads
25
Citations as of Nov 10, 2025
Google ScholarTM
Check
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.