▍1. 线性褶积
说明: 可以将目标矩阵进行线性褶积运算,用于数字信号处理(The target matrix can be linearly convoluted for digital signal processing)
说明: ecg信号处理,基线漂移,小波变换、snr mse(ECG signal processing, baseline drift, wavelet transform, SNR MSE)
说明: 主要针对道路提取程序,使用二值法和形态法(Road extraction procedures, using binary and morphological methods)
说明: 小波阈值去噪,用于对以为信号降噪处理,代码为matlab代码,亲测有效(Wavelet threshold denoising)
LeGall(5,3)小波滤波器,其计算复杂度小、存储开销低、压缩效率高,已被JPEG2000标准采用。提升小波实例c语言实现(Lifting Wavelet Example C Language Implementation)
说明: LeGall(5,3)小波滤波器,其计算复杂度小、存储开销低、压缩效率高,已被JPEG2000标准采用。提升小波实例c语言实现(Lifting Wavelet Example C Language Implementation)
根据采集的时域数据,做fft得到其频谱,并计算其功率谱密度(According to the collected time-domain data, the frequency spectrum is obtained by FFT and the power spectral density is calculated.)
说明: 可以对图像实现拉东变换,包含了原始图像与程序,可以自行修改(Radon transform of image can be realized)
关于小波变换的一些常用函数,有关多尺度变换,希望可以帮助您(Wavelet commonly used functions, on multi-scale transformation, I hope to help you)
说明: 关于小波变换的一些常用函数,有关多尺度变换,希望可以帮助您(Wavelet commonly used functions, on multi-scale transformation, I hope to help you)
关于小波变换及其应用的一本经典教材,值得学习(A classic textbook on wavelet transform and its application is worth learning)
说明: 关于小波变换及其应用的一本经典教材,值得学习(A classic textbook on wavelet transform and its application is worth learning)
说明: shearlet变换matlab工具箱,可用于图像降噪、融合(Shearlet transform matlab toolbox can be used for image denoising and fusion)
说明: 实现f-k变换,功能强大,各种滤波处理,地震波等都能用(wavelet transformF -k transform, powerful, a variety of filtering, seismic waves can be used)
实现f-k变换,功能强大,各种滤波处理,地震波等都能用(wavelet transformF -k transform, powerful, a variety of filtering, seismic waves can be used)
循环平稳信号是一类特殊的非平稳信号,其统计特征具有随时间呈周期变化的特点。旋转机械由于周期运行方式其振动信号具有循环平稳特性,因此利用循环平稳分析方法能够提取出在平稳假设下所不能得到的隐藏故障特征信息,为有效地分离和识别旋转机械早期微弱故障特征提供可能。(The cyclostationary signal is a special type of non-stationary signal whose statistical characteristics have a periodic variation with time. Due to the cyclical operation of the rotating machinery, the vibration signal has the characteristics of cyclostationary stability. Therefore, the cyclostationary analysis method can extract the hidden fault feature information that can not be obtained under the stationary assumption, which provides the possibility to effectively separate and identify the early weak fault features of the rotating machinery.)