| 基于混合神经网络的ECG数据压缩 |
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| 引用本文： | 张浙亮,吕维雪.基于混合神经网络的ECG数据压缩[J].浙江大学学报(自然科学版 ),2000,34(1):71-76. |
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| 作者姓名： | 张浙亮 吕维雪 |
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| 作者单位： | 东方通信技术中心!浙江杭州310013(张浙亮)，浙江大学生命科学与医学工程学系!浙江杭州310027(吕维雪) |
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| 摘 要： | 提出了一种基于神经网络自适应模板匹配（ＮＮＡＴＭ）的ＥＣＧ压缩方法，利用Ｋｏｈｏｎｅｎ的自组织特征映射（ＳＯＦＭ）对ＥＣＧ波形进行分类，然后根据分类结果将心搏波形送往相应的前馈网络压缩，并生成一匹配模板，最后用ＳＡＰＡ３算法对残差信号进行处理。对以２５０Ｈｚ和１１ｂｉｔ量化的ＭＩＴ／ＢＩＨ心电波型的实验表明，该方法压缩效果好于ＳＡＰＡ３算法。
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| 关 键 词： | 心电数据 数据压缩 神经网络 模板匹配 心脏疾病 |
| 修稿时间： | 1996-11-21 |
ECG data compression using neural-network-based adaptive template matching method |
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| Abstract: | A new ECG data compression method using neural\|network\|based adaptive template matching (NNATM) method is presented. To compress ECG, we used a Kohonen's self\|organizing feature map (SOFM) to classify waveforms, and sent them to correspondent multilayer feedforward neural networks to compress according to class label to generate a proper ECG template; Finally, we used SAPA3 algorithm to process the residual signals. The suggested method was evaluated by using ten kinds of MIT/BIH ECG waveforms which are sampled with 250 Hz and 11 bit/sample. The results showed that this method improved the accuracy of the reproduced signals while the compression ration was higher comparing to SAPA3 algorithm. |
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| Keywords: | electrocardiogram (ECG) data compression neural network template matching |
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