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Wavelet analysis and classification of Mitral regurgitation and normal heart sounds based on artificial neural networks

机译:基于人工神经网络的二尖瓣反流和正常心音的小波分析和分类

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摘要

The application of wavelet transform for the heart sounds signal is described. The performance of integral wavelet transform and discrete wavelet transform for heart sounds analysis is discussed. The features from heart sounds were obtained from integral wavelet transform and used to train and test the artificial neural networks (ANN). The ANN was trained by 125 training data and tested with 52 data. The classification accuracy is 94.2%.
机译:描述了小波变换在心音信号中的应用。讨论了积分小波变换和离散小波变换在心音分析中的性能。心音的特征是通过积分小波变换获得的,并用于训练和测试人工神经网络(ANN)。人工神经网络通过125个训练数据进行了训练,并用52个数据进行了测试。分类精度为94.2%。

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