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《MATAB小波分析（第2版）》张德丰 书籍配套所有源代码("MATAB wavelet analysis (Second Edition)" - Zhang Defeng, books supporting all the source code)

用于时频分析，其中包括短时傅里叶变换、小波变换、脊线提取以及一些信号的生成等。(For time-frequency analysis, including short-time Fourier transform, wavelet transform, ridge extraction and generate some signals and so on.)

二维双密度双树（复数）小波变换包。包含基于小波变换的基本的阈值处理运算。(2-D Double-Density Complex Wavelet Transform。There are two versions of the 2-D double-density dual-tree DWT: (1) The 2-D double-density dual-tree real-oriented DWT, which is 2-times expansive, and (2) The 2-D double-density dual-tree complex-oriented DWT, which is 4-times expansive.)

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)

单分量仿真信号进行小波变换后，小波脊线的提取(After the simulation of a single component signal wavelet transform, wavelet ridge extraction)

二代小波harr变换整数小波变换，适合图像处理专业人员参考(Second generation wavelet transform Harr integer wavelet transform for image processing professionals reference)

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：  基于vc++6.0 的图像对比度拉伸操作(vc 6.0 on the image contrast stretching operation)

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。(Wavelet transform (WT) is a new transform analysis method. It inherits and develops the idea of localization of short-time Fourier transform and overcomes the shortcomings that window size does not vary with frequency. It can provide a frequency-dependent The Time-Frequency window is ideal for time-frequency analysis and processing of signals. Its main feature is that by transforming some features that can fully highlight some aspects of the problem, the localization of the time (space) frequency can be analyzed, and the signal (function) can be gradually and multi-scale refined by the scaling operation, finally reaching the high frequency Time subdivision, frequency subdivision at low frequencies, can automatically adapt to the requirements of time-frequency signal analysis, which can focus on any details of the signal to solve the difficulties of Fourier transform has become a major breakthrough in the scientific method since Fourier transform.)

基于小波变换的心电信号预处理MATLAB源代码(The heart preprocessind based on wavelet transform)