A Novel Research on Feature Extraction of Acoustic Targets based on Manifold Learning

被引：0
|
作者：
Liu, Hui [1 ]
Wang, Wei [1 ]
Yang, Jun-an [1 ]
Zhen, Liu [1 ]
机构：
[1] PLA, Inst Elect Engn, Hefei, Anhui, Peoples R China
来源：
2015 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATIONS (CSA) | 2015年
关键词：
acoustic targets recognition; feature extraction; manifold learning; DIMENSIONALITY REDUCTION;
D O I：
10.1109/CSA.2015.52
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In order to overcome the robustness of low altitude passive acoustic target recognition, the manifold learning was originally introduced to the feature extraction of acoustic targets. Based on the classical algorithm of manifold learning, the paper studied and discussed the low dimensional manifold in the frequency-domain of acoustic signals. This method was applied to acoustic target recognition problem with two data sets to verify its effectiveness, after which the performance was analyzed. The result indicated that the manifold learning can discover the intrinsic feature and increase the accuracy and robustness of low altitude passive acoustic target recognition system.
引用
收藏
页码：227 / 231
页数：5
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