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主成分分析在舰船辐射噪声分类识别中的应用
引用本文:张岩,尹力.主成分分析在舰船辐射噪声分类识别中的应用[J].应用声学,2009,28(1):20-26.
作者姓名:张岩  尹力
作者单位:中国科学院声学研究所综合声纳实验室,北京,100190
摘    要:主成分分析(PCA)是经典的多元统计分析方法,在处理多变量综合问题方面有比较突出的优势。本文主要探讨了主成分分析在舰船辐射噪声信号分类识别中的应用。在经典功率谱的基础上尝试将PCA技术运用在两种不同的方法中,对两种舰船辐射噪声进行了特征提取和分类识别,得到了较好的效果。

关 键 词:主成分分析  舰船辐射噪声  功率谱  特征提取  分类识别

Application of principal component analysis to ship-radiated noise classification and recognition
Zhan Gyan and yin Li.Application of principal component analysis to ship-radiated noise classification and recognition[J].Applied Acoustics,2009,28(1):20-26.
Authors:Zhan Gyan and yin Li
Institution:(Institute of Acoustics,Chinese Academy of Sciences,Beijing 100190)
Abstract:Principal Component Analysis is a classic multivariate statistical analysis method, which has obvious advantage in the integrated multi-variable problem.This paper works on the application of PCA to the ship-radiated noise classification and recognition. By using the PCA technology to two different methods on the basis of classic power spectrum, we extract features of 2 different types of ship-radiated noises and complete the classification and recognition.The results indicate that the method is effective and valid.
Keywords:Principal Component Analysis  Ship-radiated noise  Power spectrum  Feather extraction  Classification and recognition
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