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该程序是用小波函数构建神经网络的源程序。用以分析心电信号、脑电信号等等。-that the procedure was constructed using wavelet neural network function of the source. For the analysis of ECG, EEG, and so on.
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利用bp神经网络的方法来实现ecg信号st段的模式识别。-The use of bp neural network approach to the realization of ecg signal st paragraph of pattern recognition.
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摘要:心电图ST段对心脏疾病的诊断具有重要意义。在正确读取采集于郑州大学一附院的运动心电图数据基础上,利用小波变换更准确地确定其ST段的起始和终止位置,初步探讨了BP神经网络用于心电图ST段识别的方法,并用此方法识别出心电图ST段的三种类型—正常、水平压低和抬高。实验结果较好。
-Abstract: ECG ST segment on the diagnosis of heart disease is important. Collected in the correct reading o
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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
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神经网络算法RBF分离母体心电和胎儿心电信号-RBF neural network algorithm for separation of maternal ECG and fetal ECG
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利用径向基函数神经网络，完成ECG信号的非线性拟合，进而提取出胎儿心电信号-Radial basis function neural network to complete the non-linear fitting of the ECG signal, and then extract the fetal ECG
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In this paper analysis of „ Electrocardiogram (ECG) PQRSTU-waveforms and prediction of
particular decease infection or state of a patient is done using Genetic Algorithm and Artificial Neural
Network (ANN), precise Electrocardiogram (ECG) class
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内含心电信号数据及运用MATLAB写的源代码，关于神经网络控制，对球谐函数图形进行仿真。- ECG data and includes source code written in MATLAB, On neural network control, Of spherical harmonics graphic simulation.
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是一种双隐层反向传播神经网络，内含心电信号数据及运用MATLAB写的源代码，本程序的性能已经超过其他算法。- Is a two hidden layer back propagation neural network, ECG data and includes source code written in MATLAB, This program has exceeded the performance of other algorithms.
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包括面积、周长、矩形度、伸长度，关于神经网络控制，内含心电信号数据及运用MATLAB写的源代码。- Including the area, perimeter, rectangular, elongation, On neural network control, ECG data and includes source code written in MATLAB.
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Using MATLAB dynamic clustering or iterative self-organizing data analysis, BP neural network function fitting and pattern recognition, ECG data and includes source code written in MATLAB.
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ECG data and includes source code written in MATLAB, The entire training process BP neural network, Convolution operation is intended to signal and image rendering.
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ECG data and includes source code written in MATLAB, On neural network control, Very suitable for the study using computer vision.
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利用小波变换进行ECG特征识别，利用神经网络进行分类从而进行身份识别(Identification of identity using wavelet transform)
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这是一个为1D心电图数据训练而设计的神经网络。(this is a Covoluntional Neural Network deisigned for 1D ECG data training.)
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使用卷积神经网络实现心电异常分类，内含损失函数，验证集、测试集等(ECG anomaly classification using convolutional neural network)
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