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首页> 外文期刊>International Journal of Performability Engineering >Optimized VMD-Wavelet Packet Threshold Denoising based on Cross-Correlation Analysis
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Optimized VMD-Wavelet Packet Threshold Denoising based on Cross-Correlation Analysis

机译：基于交叉相关分析优化的VMD-小波分组阈值去噪

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摘要

To address the problem that wavelet packet denoising is unable to process signals with strong white noise, an optimized VMD-wavelet packet threshold denoising method based on cross-correlation analysis is proposed. This method combines the advantages of VMD and wavelet packet denoising. By decomposing the noisy signal into several modal components using VMD, the excellent modal components are selected from all modal components according to the cross-correlation analysis based critical correlation coefficient. After that, these excellent modal components are processed using the wavelet packet threshold denoising method. Experimental results show that the proposed method has the advantage of denoising signal with strong white noise, which preserves the effective components of signal, overcomes the blindness of traditional VMD denoising methods and ensures the authenticity of the denoised signal.
机译：为了解决小波分组去噪不能处理具有强白噪声的信号的问题，提出了一种基于互相关分析的优化的VMD-小波分组阈值去噪方法。 该方法结合了VMD和小波包去噪的优点。 通过使用VMD将噪声信号分解成几种模态分量，根据基于基于互相关系数的互相关分析，从所有模态分量中选择优异的模态分量。 之后，使用小波分组阈值去噪方法处理这些优异的模态分量。 实验结果表明，该方法具有强大的白噪声的发出信号的优点，这保留了信号的有效组分，克服了传统的VMD去噪方法的失明，并确保了去噪信号的真实性。

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