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Guanni Ji

As seen in: Frontiers, MDPI
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Articles by Guanni Ji

Comparative Study on Feature Extraction of Marine Background Noise Based on Nonlinear Dynamic Features

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By Guanni Ji, Yu Wang, Fei Wang
| MDPI
3. Feature Extraction of MBN Based on Nonlinear Dynamic Features 3.1. Marine Background Noise Four types of measured MBN are selected from the dataset of the National Marine Park Service [30] to study and compare the feature extraction method based on nonlinear dynamic features, including heavy rain on the sea surface, light wind on the sea surface, moderate wind on the sea surface, and wind and ship noise on underwater hydrophones, named H-R, L-W, M-W, and W-S, respectively.
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Analysis of the synergistic complementarity between bubble entropy and dispersion entropy in the application of feature extraction

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By xinru jiang, Ke Qu, Govind Vashishtha, Guanni Ji
| Frontiers
1School of Automation and Information Engineering, Xi’an University of Technology, Xi’an, China 2Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing, Xi’an University of Technology, Xi’an, China Most of the existing studies on the improvement of entropy are based on the theory of single entropy, ignoring the relationship between one entropy and another.
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