文件名称:ann
- 所属分类：
- 人工智能/神经网络/遗传算法
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- [PDF]
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- 2012-11-26
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- 260kb
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- 罗**
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介绍了一种基于神经网络白化匹配滤波器的QRS 波检测方法。我们用神经网络白化匹配滤波器来处
理ECG 信号的低频成分, 模拟其非线性及非稳态的特性。处理后的信号中含有ECG 中大部分高频成分, 让其通过
一线性匹配滤波器来检测QRS 波及其位置。对于大噪声的ECG 信号, 在匹配滤波器后加差分滤波, 取平方及滑动
平均等处理, 提高检测正确率。使用这种方法我们对M IT?B IH 心电信号数据库中噪声比较大的105号数据进行的
处理, 检测正确率为9912 。作为对比, 用数字带通滤波器检测, 正确率为9718 。-Introduced a whitening matched filter based on neural network of the QRS wave detection. We use neural networks to handle the whitening matched filter low frequency ECG signal to simulate the nonlinear and non-steady state characteristics. Processed ECG signal contains most of the high frequency components, let through a linear matched filter to detect the QRS wave and position. For large noise the ECG signal after the matched filter plus differential filter, such as taking the square and the moving average processing, improve the detection accuracy. Using this method we have M IT?B IH noise ECG database of 105 large data processing, testing rate was 9912 correct. In contrast, detection with digital band-pass filter, the correct rate of 9718 .
理ECG 信号的低频成分, 模拟其非线性及非稳态的特性。处理后的信号中含有ECG 中大部分高频成分, 让其通过
一线性匹配滤波器来检测QRS 波及其位置。对于大噪声的ECG 信号, 在匹配滤波器后加差分滤波, 取平方及滑动
平均等处理, 提高检测正确率。使用这种方法我们对M IT?B IH 心电信号数据库中噪声比较大的105号数据进行的
处理, 检测正确率为9912 。作为对比, 用数字带通滤波器检测, 正确率为9718 。-Introduced a whitening matched filter based on neural network of the QRS wave detection. We use neural networks to handle the whitening matched filter low frequency ECG signal to simulate the nonlinear and non-steady state characteristics. Processed ECG signal contains most of the high frequency components, let through a linear matched filter to detect the QRS wave and position. For large noise the ECG signal after the matched filter plus differential filter, such as taking the square and the moving average processing, improve the detection accuracy. Using this method we have M IT?B IH noise ECG database of 105 large data processing, testing rate was 9912 correct. In contrast, detection with digital band-pass filter, the correct rate of 9718 .
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基于神经网络的波型检测方法.pdf