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中文核心期刊

基于小波变换的舰船辐射噪声特征提取

Feature extraction of ship radited noises based on wavelet transform

  • 摘要: 本文将小波变换用于舰船辐射噪声特征分析。先用Mallat快速算法实现信号的多尺度分解,然后进行各级小波的谱特征和波形结构特征提取,最后将这些特征与原始信号的特征输入同一类型神经网络分类器,进行分类比较。结果表明,小波变换使信号的谱类别特征和波形结构特征有了明显增强,且能压缩特征空间的维数。

     

    Abstract: Wavelet transform was used for extracting features of ship radited noises in this paper.Firstly, Mallat ajgorithm was employed to decompose signals. Secondly, features based on power spectrum and wave shape of the decomposed signals were extracted. Finally, these features were compared with the one of original signal in a neural network classifier. Results show that wavelet transform can enhance the spectrum and shape features of the signal and can reduce the number of dimensions of the feature space.

     

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