wavelet4

说明：  本程序是卡尔曼滤波的源程序包，请大家分享.(Kalman filtering of the source packet, please share.)

本代码是小波包学习和使用的初学代码，简单改造可对信号进行滤波，去噪，实现我们需要的各种功能(xiaobobao )

基于小波变换的图像压缩感知 并且进行OMP重建 对压缩感知的性能与采样点数进行性能分析与比较(Image compression based on wavelet transform perception and the OMP reconstruction performance of compressed sensing and sample analysis and comparison of performance points)

描述电磁波（电场或磁场）在自由空间传播的Matlab程序。(Description of electromagnetic waves (electric or magnetic) in free-space propagation of Matlab procedures.)

用小波变换去除荧光背景，扣除基线。matlab(Remove fluorescence background, net baseline using wavelet transform. matlab)

小波十讲中文、切边优化版本，适合直接在kindle阅读(<Ten Lectures on Wavelets>)

Fast wavelet transforms and numerical algorithms 1

心电信号的预处理。高通滤波器，低通滤波器，50Hz带阻滤波器。(The preprocessing of the ECG signal. High-pass filter, low pass filter, 50Hz band-stop filter....)

小波变换对电能质量暂态信号的分析和运用，包含电压骤升、骤降等(Wavelet transform for power quality analysis and the use of transient signals, including voltage dips, swells, etc.)

说明：  提出了一种结合SVD的小波变换方法，对其在外弹道测量数据中的野值剔除进行了研究。对观测数据进行小波分解，将小波分解后的近似分量和细节分量组合实现相空间重构，作为SVD方法的输入观测矩阵，根据奇异 熵增量准则，对奇异值进行筛选，根据SVD逆变换重构原信号。这一方法克服了Hankel矩阵相空间构建方法数据 端点失真问题。以小波分解后分量重构的相空间可以满足正交性，进一步提高了SVD进行数据降噪和野值检测的精度。仿真数据和试验数据处理结果证明了这一方法的有效性。(Proposed a method of combining the SVD wavelet transform its outer ballistic measurement data in excluding outliers were studied. Observational data on wavelet decomposition, wavelet decomposition of the approximate combined component and detail component to achieve the phase space reconstruction, as the input observation matrix SVD method, based on singular entropy increment standards, singular value filter, according to the inverse transform heavy SVD structure of the original signal. This approach overcomes the Hankel matrix phase space construction method data endpoint distortion. Wavelet decomposition component of reconstruction phase space satisfy orthogonality, to further improve the SVD for data noise reduction and outlier detection accuracy. Simulation data and experimental data processing results prove the effectiveness of this approach.)