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Description: 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 used wavelet build neural networks of the source. For the analysis of ECG, EEG, etc..
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Size: 1299 |
Author: 沈进旗 |
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Description: 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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Size: 1451 |
Author: sandy4000 |
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Description: 用MATLAB实现的网络设计与测试程序，为神经网络理论的应用-MATLAB network design and testing procedures for the neural network theories in the
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Size: 1024 |
Author: 周岩 |
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Description: 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 used wavelet build neural networks of the source. For the analysis of ECG, EEG, etc..
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Size: 1024 |
Author: 沈进旗 |
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Description: 这是神经网络中,基于sfom算法的数字识别系统，能够识别0-9共十个数字，并同时给出识别误差！！自己编的！-This is the neural network, sfom algorithm based on the number of identification system 0-9 to identify a total of 10 figures, and also given the recognition error! ! Developed!
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Size: 1613824 |
Author: 彭涛 |
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Description: 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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Size: 1024 |
Author: sandy4000 |
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Description: rbf神经网络的matlab程序,运算时间短,程序简单-rbf neural network matlab procedures, computing time is short, simple procedures
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Size: 1024 |
Author: 小伟 |
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Description: 利用人工神经网络算法对人体心电信号进行特征提取并进行识别-Using artificial neural network algorithm on human ECG feature extraction and recognition
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Size: 9803776 |
Author: |
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Description: 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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Size: 359424 |
Author: 谢阳 |
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Description: 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 of the first affiliated hospital of Zhengzhou University in exercise ECG data based on the use of wavelet transform to more accurately determine the ST segment of the start and end position, discussed the BP neural network for ECG ST-recognition method, and use this method to identify three types of ECG ST segment- the normal, the level of depression and elevation. Experimental results are good.
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Size: 97280 |
Author: Lily |
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Description: 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 .
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Size: 266240 |
Author: 罗朝辉 |
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Description: The early detection of arrhythmia is very important
for the cardiac patients. This done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different types of arrhythmias. In this paper, we present three
different algorithms of features extraction: Fourier transform
(FFT), Autoregressive modeling (AR), and Principal Component
Analysis (PCA). The used classifier will be Artificial Neural
Networks (ANN). We observed that the system that depends on
the PCA features give the highest accuracy. The proposed
techniques deal with the whole 3 second intervals of the training
and testing data. We reached the accuracy of 92.7083
compared to 84.4 for the reference that work on a similar
data.-The early detection of arrhythmia is very important
for the cardiac patients. This is done by analyzing the
electrocardiogram (ECG) signals and extracting some features
from them. These features can be used in the classification of
different types of arrhythmias. In this paper, we present three
different algorithms of features extraction: Fourier transform
(FFT), Autoregressive modeling (AR), and Principal Component
Analysis (PCA). The used classifier will be Artificial Neural
Networks (ANN). We observed that the system that depends on
the PCA features give the highest accuracy. The proposed
techniques deal with the whole 3 second intervals of the training
and testing data. We reached the accuracy of 92.7083
compared to 84.4 for the reference that work on a similar
data.
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Size: 273408 |
Author: Amit Majumder |
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Description: 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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Size: 1024 |
Author: 刘家强 |
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Description: 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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Size: 82944 |
Author: 占海龙 |
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Description: ECG Signal Analysis and Classification using Data Mining and Artificial Neural Networks
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Size: 316416 |
Author: behrooz |
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Description: 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) classification to diagnose patient‟ s condition is essential.
For classification of such difficult-to-diagnose-signals, i.e. ECG signal, classification is performed using
various pulses,
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Size: 4096 |
Author: mohammad |
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Description: 非常适合计算机视觉方面的研究使用,包括最小二乘法、SVM、神经网络、1_k近邻法,内含心电信号数据及运用MATLAB写的源代码。- Very suitable for the study using computer vision, Including the least squares method, the SVM, neural networks, 1 _k neighbor method, ECG data and includes source code written in MATLAB.
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Size: 9216 |
Author: manfan |
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Description: 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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Size: 6144 |
Author: fingfuimoubai |
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Description: 包括调制，解调，信噪比计算，内含心电信号数据及运用MATLAB写的源代码，包括最小二乘法、SVM、神经网络、1_k近邻法。- Includes the modulation, demodulation, signal to noise ratio calculation, ECG data and includes source code written in MATLAB, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.
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Size: 5120 |
Author: fhqwfmsx |
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Description: 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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Size: 16384 |
Author: D_w223 |
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