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离散小波变换的简单程序，适合初学者学习，附有通用函数。(Simple procedures discrete wavelet transform, suitable for beginners to learn, with common functions.)

形态成分析（MCA）用于图像分割与去噪的实验代码(Form into analysis (MCA) for image segmentation and denoising experimental code)

用于进行小波变换，对原始的光谱图像数据进行预处理(Used wavelet transform, the original spectral image data preprocessing)

去除在心电信号采集过程中混入的肌电干扰、工频干扰、基线漂移等噪声信信号，避免噪声对心电信号特征点的识别与提取造成误判漏判 已通过测试。 (Remove the EMG interference mixed with the signal acquisition process in mind, frequency interference, baseline drift and noise channel signal to avoid noise caused by the misjudgment of the Missing has been tested on ECG feature identification and extraction.)

对含噪声信号进行小波变换；对变换得到的小波系数进行某种处理，以去除其中包含的噪声；对处理后的小波系数进行小波逆变换，得到去噪后的信号(Containing noise signal wavelet transform the wavelet transform coefficients to a treatment to remove the noise contained therein the treated wavelet inverse wavelet transform coefficients to obtain a denoised signal)

基于gabor小波变换的论文，对做人脸识别很有用(Gabor wavelet transform-based papers, do face recognition is useful)

对地震数据进行gabor反褶积处理，有实例验证方法，简单易懂(The seismic data are processed by Gabor deconvolution.There are examples of methods to verify, easy to understand)

实现基于离散小波（dwt）的奇异值（svd）分解算法的实现(Decomposition algorithm based on singular value of the discrete wavelet (dwt) (svd))

图像小波变换，小波变换（wavelet transform，WT）是一种新的变换分析方法，它继承和发展了短时傅立叶变换局部化的思想，同时又克服了窗口大小不随频率变化等缺点，能够提供一个随频率改变的“时间-频率”窗口，是进行信号时频分析和处理的理想工具。它的主要特点是通过变换能够充分突出问题某些方面的特征，能对时间（空间）频率的局部化分析，通过伸缩平移运算对信号（函数)逐步进行多尺度细化，最终达到高频处时间细分，低频处频率细分，能自动适应时频信号分析的要求，从而可聚焦到信号的任意细节，解决了Fourier变换的困难问题，成为继Fourier变换以来在科学方法上的重大突破。(Image Wavelet Transform)

说明：  紧支撑小波基的构造。 以Daubechies小波滤波器系数为例，推导出小波函数及尺度函数，并画出其图像. void Convolution(double* pShortData, int nShort, double* pLongData, int nLong) int CalcScaleFunction(double* pOutData) int CalcWaveletFunction(double* pOutData) Convolution()不是通用的离散卷积代码，而是简单地实现了后面两个函数需要的离散卷积，它要求输入的前一个数组长度小于后一数组长度，而且卷积结果就直接覆盖存储在后一数组中。CalcScaleFunction()计算尺度函数，CalcWaveletFunction()计算小波函数。 (Compactly supported wavelet bases constructed. To Daubechies wavelet filter coefficients as an example, the derived wavelet function and scaling function, and draw their images. Void Convolution (double* pShortData, int nShort, double* pLongData, int nLong) int CalcScaleFunction (double* pOutData) int CalcWaveletFunction ( double* pOutData) Convolution () instead of generic discrete convolution code, but simply the realization of a function behind the need for two discrete convolution, which requires input before an array length is less than the array length of the latter, but the result of convolution directly covered by the latter is stored in the array. CalcScaleFunction () calculated scaling function, CalcWaveletFunction () calculation of wavelet function.)