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基于提升小波变换的MFCC在目标识别中的应用
引用本文:石超雄,李钢虎,何会会,赵妮.基于提升小波变换的MFCC在目标识别中的应用[J].声学技术,2014,33(4):372-375.
作者姓名:石超雄  李钢虎  何会会  赵妮
作者单位:西北工业大学航海学院, 陕西西安 710072;西北工业大学航海学院, 陕西西安 710072;西北工业大学航海学院, 陕西西安 710072;西安邮电大学通信与信息工程学院, 陕西西安 710072
摘    要:水下环境噪声对被动声呐目标的分类识别影响显著,为了提高水声信号识别系统对环境噪声的鲁棒性,采用提升小波变换方法提取MFCC特征,对水下被动声呐目标进行分类和识别。仿真实验表明,与传统MFCC和小波变换的MFCC相比,在信噪比相近的情况下,提升小波变换方法提取MFCC具有识别率较高、对噪声鲁棒性较好的显著优点。

关 键 词:提升小波变换  Mel频率倒谱系数  分类识别
收稿时间:2013/3/14 0:00:00
修稿时间:2013/6/4 0:00:00

Application of the lifting wavelet transform based MFCC in target identification
SHI Chao-xiong,LI Gang-hu,HE Hui-hui and ZHAO Ni.Application of the lifting wavelet transform based MFCC in target identification[J].Technical Acoustics,2014,33(4):372-375.
Authors:SHI Chao-xiong  LI Gang-hu  HE Hui-hui and ZHAO Ni
Affiliation:School of Marine Engineering, Northwestern Polytechnical University, Xi''an 710072, Shaanxi, China;School of Marine Engineering, Northwestern Polytechnical University, Xi''an 710072, Shaanxi, China;School of Marine Engineering, Northwestern Polytechnical University, Xi''an 710072, Shaanxi, China;School of communication and Information Engineering, Xi''an University of Posts and Telecommunications, Xi''an 710072, Shaanxi, China
Abstract:The underwater noise could badly affect the results of passive sonar classification and target recognition. In order to improve the robustness of underwater acoustic signal identification system against environmental noise, a new MFCC feature extraction method based on lifting wavelet transform is proposed. Experimental results show that, compared with the traditional MFCC, the wavelet transform MFCC method for underwater acoustic signal classification and identification works better under the same SNR, which significantly improves the robustness against noise.
Keywords:lifting wavelet transform  Mel frequency cepstrum coefficient  classification and recognition
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