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通过学习小波变换原理，自行编写小波函数，不用matla自带小波函数(Wavelet transform principle, by learning to write wavelet function, need not matla with wavelet function)

通过设计Visual C程序源码对简单易懂的一维信号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波与Haar小波变换，从而的到小波分解系数；再通过改变分解的到的各层高频系数数进行信号的小波重构达到消噪噪的目的。在这一程序源码实现的过程中能直观地理解信号小波分解重构的过程与在信号消噪中的重要作用，和在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。 可直接 (Design Visual C program source code on a simple one-dimensional signal with a Gaussian white noise Daubechies wavelet, Morlet wavelet and Haar wavelet transform, and thus to the wavelet coefficients and then change the decomposition to each storey wavelet reconstruction frequency coefficient of the number of signal to noise canceling noise. In the process of realization of this program source code can be intuitively understood the signal wavelet decomposition and reconstruction process and an important role in signal denoising, and the selection coefficient in the high frequency coefficients of the layers of the weight of processing noise cancellation signal impact. Can be directly)

Tetrolet变换的原代码，一种稀疏表示的小波变换，由haar变换改进得到(Tetrolet transform the original code, a sparse representation of the wavelet transform, haar transform improved)

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)

设计陷波滤波器，建立原始信号，对其采样，将采样信号通过滤波器进行滤波(Design trapped wave filter, establish the original signal, the sampling, will sampling signal through the filter to filter)

离散小波变换与离散小波反变换 快速小波变换（Mallat小波分解算法）：对一幅图像做2级小波分解（离散小波变换）与合成（离散小波反变换）(Discrete wavelet transform and discrete wavelet inverse transform fast wavelet transform (Mallat wavelet decomposition): For an image to do 2 wavelet transform (DWT) and synthesis (discrete wavelet inverse transform))

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

基于小波变换的信号去噪技术，简单的一维小波去噪程序(Signal de-noising based on wavelet transform technique, a simple one-dimensional wavelet denoising procedure)

Second generation wavelets and applications

自适应滤波器中的rls和lms两种算法matlab仿真比较程序。(Rls adaptive filter and the LMS algorithm matlab simulation comparison of two procedures.)