| 陈丹,李京华,黄根全,许俊峰.基于主分量分析的声信号特征提取及识别研究[J].声学技术,2005,(1):39~41,45 |
| 基于主分量分析的声信号特征提取及识别研究 |
| Feature extraction and acoustic signal recognition using principal components analysis |
| 投稿时间：2004-05-17 修订日期：2004-07-12 |
| DOI： |
| 中文关键词: 主分量分析(PCA) 特征提取 分类器 目标识别 |
| 英文关键词: principal component analysis feature extraction classifier target recognition |
| 基金项目:国防重点实验室预研基金资助项目(51454020101HK0307);西北工业大学科技创新基金资助项目(2003CR080001) |
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| 中文摘要: |
| 主分量分析(PCA)是统计学中分析数据的一种有效方法。研究了基于这种算法对四种战场目标的声信号进行特征提取,获得了低维的特征类器对声目标进行分类,分类结果准确率较高,均获得满意的实验效果 |
| 英文摘要: |
| This paper proposes an algorithm of feature extraction from acoustic signals based on principal component analysis (PCA). Features of four types of acoustic signals of battlefield target are extracted and low-dimcnsion feature vectors obtained with this technique. K-nearest neighbor classifier and BP neural network classifier are designed for the acoustic target classification. Satisfactory experimental results have been obtained with classification accuracy reaching as high as 86%. |
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