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java小波变换的实现，包括哈尔小波，以及在这基础上改进的小波实现。(The implementation of Daubechies wavelets.)

小波变换是一种非常重要的时频分析方法，研究小波变换对于地震处理研究有着非常重要的作用(Wavelet transform is a important tool for time-frequency,which plays an important part in the seismic processing.)

小波阈值法去噪的程序，其中有关于信噪比和均方根误差的公式(wavelet denoising)

用matlab编程实现了ridgelet多尺度变换，实现了图像的解析，重构，压缩等功能(Ridgelet with matlab programming a multi-scale transformation to achieve the image resolution, reconstruction, compression and other functions)

使用小波包分析信号的MATLAB程序，对初学者有用~~~~·( analysis Signal by Wavelet packet..matlab~~)

心电信号分析 （1）设计滤波器，实现对心电信号的噪声抑制和基线纠漂。 （2）时域分析：R波检测算法与实现. （3）功率谱分析：对消噪后的信号进行功率谱分析。要求计算信号的功率谱，功率谱峰值，峰值频率。 (ECG Analysis (1) design filters to achieve noise suppression of ECG and baseline drift correction. (2) time-domain analysis: R-wave detection algorithm and implementation (3) The power spectrum analysis: noise cancellation signal after the power spectrum analysis. Require calculation of the signal power spectrum, peak power spectrum, peak frequency.)

Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as complex-valued dual-tree wavelets are considered for their highly directional representation, while bivariate shrinkage is adapted to their multiscale decomposition structure to provide the requisite sparsity constraint. Smoothing is achieved via a Wiener filter incorporated into iterative projected Landweber compressed-sensing recovery, yielding fast reconstruction. The proposed approach yields images with quality that matches or exceeds that produced by a popular, yet computationally expensive, technique which minimizes total variation. Additionally, reconstruction quality is substantially superior to that from several prominent pursuits-based algorithms that do not include any smoothing

对信号f(x)进行三层小波变换，得到小波系数d1,d2,d3和逼近系数a3，我想求出各个频率段的能量（能量=小波系数的平方和），很不错的应用程序(The signal f (x) for three wavelet transform, wavelet coefficients d1, d2, d3 and approximation coefficients a3, I would like to find the energy of each frequency band (energy = sum of squared wavelet coefficients), very good application)

高斯滤波.这段代码主要用于以为信号的高斯滤波。(Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter)

用小波方法把脑电信号进行频段分解，并画出图形(Using wavelet method to decompose the eeg signals into frequency bands, and draw the graph)