英文论文


文献类型
Journal article (JA)
题名
Integrated optimization of underwater acoustic ship-radiated noise recognition based on two-dimensional feature fusion
作者
Ke, Xiaoquan; Yuan, Fei; Cheng, En
作者单位
[Ke, Xiaoquan; Yuan, Fei; Cheng, En] Xiamen Univ, Minist Educ, Key Lab Underwater Acoust Commun & Marine Informa, Xiamen 361005, Fujian, Peoples R China.
通讯作者地址
Xiamen Univ, Minist Educ, Key Lab Underwater Acoust Commun & Marine Informa, Xiamen 361005, Fujian, Peoples R China.
Email
yuanfei@xmu.edu.cn
ResearchID
ORCID
期刊名称
Applied Acoustics
出版社
Elsevier Ltd
ISSN
0003-682X
出版信息
2020-02, 159:-.
JCR
3
影响因子
2.639
ISBN
基金
National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [61871336, 61571377, 61771412]; Fundamental Research Funds for the Central UniversitiesFundamental Research Funds for the Central Universities [20720180068]
会议名称
会议地点
会议开始日期
会议结束日期
关键词
Acoustic noise measurement; Correlation methods; Principal component analysis; Ships; Underwater acoustics; Wavelet decomposition
摘要
Feature fusion methods are introduced to ship-radiated noise recognition in this paper. Wavelet packet (WP) decomposition is used to decompose the ship-radiated noise into multiple different subbands. By considering the features extracted from the different subbands reflecting different characteristics of the ship-radiated noise, a two-dimensional feature fusion (2DFF) scheme is proposed to fuse the features extracted from the different subbands. Principal component analysis (PCA) and canonical correlation analysis (CCA) are used in the 2DFF scheme. Then, a so-called discriminative ability improving (DAI) strategy is proposed to improve the discriminative ability of the extracted features. Starting at the 2DFF, a processing chain of feature fusion and ship-radiated noise recognition is designed and jointly optimized to the task. The 2DFF scheme and DAI strategy are tested on real ship-radiated noise data recorded. Experimental results indicate that compared with the baseline, the 2DFF scheme can improve 7.25% of recognition accuracy. Experimental results also show that the DAI strategy can further improve the recognition accuracy of 13.10%. (C) 2019 Elsevier Ltd. All rights reserved.
一级学科
Acoustics
WOS入藏号
WOS:000502894900008
EI收录号
20194107524520
DOI
10.1016/j.apacoust.2019.107057
ESI
PHYSICS
收录于
SCIE, EI

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