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Heart Sound Feature Extraction Based on Wavelet Singular Entropy

机译:基于小波奇异熵的心音特征提取

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摘要

After analyzing the advantages and disadvantages of current methods of heart sound feature extraction, a new method based on wavelet transform, singular value decomposition and information entropy is put forward. In this method, firstly the heart sound is decomposed by wavelet transformation. Then the singular value of the sub-bands containing heart sound information is obtained by decomposition. Finally, according to the constructed wavelet singular entropy, the entropy of the above singular value is obtained. By comparing the wavelet singular entropy of normal heart sound signal with the several heart sound signals with pathological information, wavelet singular entropy can be found a good characterization of heart sound.
机译:在分析了目前心音特征提取方法的优缺点之后,提出了一种基于小波变换,奇异值分解和信息熵的新方法。在这种方法中,首先通过小波变换分解心音。然后,通过分解获得包含心音信息的子带的奇异值。最后,根据构造的小波奇异熵,得到上述奇异值的熵。通过将正常心音信号的小波奇异熵与几种带有病理信息的心音信号进行比较,可以发现小波奇异熵很好地表征了心音。

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