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[AI-NN-PRfirbynna

Description: 此程序为本人编写的神经网络法设计1型FIR滤波器的程序,读者读此程序后,可以很深刻地理解如何用BP网络和LMS算法来设计滤波器。 只需更改程序中的H值,即可生成各种低通,高通,带通,带阻滤波器。程序运行结果可得到滤波器系数,幅频曲线和衰减曲线。 可通过更改迭代步长和误差极限来调整滤波器特性。-I prepared for this procedure the neural network type 1 FIR filter design procedures, the reader after reading this program, it is a profound understanding of how to use BP network and the LMS algorithm to design filters. Just change the procedures in H values, to generate a variety of low-pass, high pass, band-pass, band stop filter. Program is running the results of available filter coefficients, amplitude-frequency curve and the attenuation curve. Can change the iteration step size and error to adjust the filter characteristics of the limit.
Platform: | Size: 1024 | Author: 黄翔东 | Hits:

[matlabLP

Description: 基于径向基神经网络的算法逼近低通滤波器,用Matlab编程实现-Based on RBF Neural Network Approximation algorithm low-pass filter, using Matlab programming
Platform: | Size: 1024 | Author: | Hits:

[AI-NN-PRann

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 .
Platform: | Size: 266240 | Author: 罗朝辉 | Hits:

[matlabcode

Description: 三道题,包括1:用多层感知器(MLP)神经网络误差反向传播(BP)算法实现异或问题:2:用奇阶互补法设计两带滤波器组(高、低通互补),进而实现四带滤波器组 3:估计其功率谱-Three questions, including: 1 using multilayer perceptron ( MLP ) neural network and error back propagation ( BP ) algorithm to realize the XOR problem: 2: the odd order complementary method in the design of two-band filters ( complementary high, low pass ), so as to realize the four band filter group 3: to estimate the power spectrum
Platform: | Size: 106496 | Author: 严菲 | Hits:

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