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舰船噪声的1 \frac12维谱特征提取

Feature extraction of ship-radiated noise by 1 \frac12 spectrum

  • 摘要: 证明了1\frac12维谱的几个基本性质,分析了由此产生的几种优良性能:可加强成整数倍谐波信号的基频分量,抑制高斯有色噪声及对称分布的噪声;剔除非二次相位耦合的谐波分量。在此基础上,将1\frac12维谱应用于舰船噪声的目标特征分析,提出井提取了7个特征量。经过神经网络分类器的分类识别,取得了较高的识别率:A类船的正确识别率为90%,B类船的为91.3%,C类船的为85.7%。

     

    Abstract: The properties of 1 \frac12 spectrum are proved and performances are analyzed in this paper. By means of the spectrum, the fundamental frequency component of the harmonic signals can be enhanced. Gaussian color noise and symetrical distribution noise can be canceled. And non-quadratic phase coupling harmonic components can be eliminated. The ship-radiated noise is analyzed and its 7 features are extracted with the spectrum. In light of B-P artificial neural network, three type ships are classified according to their features. The correct classification rates about the three type ships A, B and C are 90%, 91.3% and 85.7%, respectively.

     

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