小波对图像的二次压缩.

说明：  使用小波变换技术实现图像分割，利用matlab编程实现(Using wavelet transform technology to achieve image segmentation, matlab programming)

EEG signal classification using wavelet feature extraction

shearlet图像融合的源代码，速度很快，做毕业设计的可以参考(shearlet fusion source code, very fast, do graduate design can refer to)

小波神经网络实现短期电力负荷预测，神经网络模型及其BP学习算法。 (Wavelet neural network short term load forecasting, neural network model and BP learning algorithm.)

关于小波包变化的，特征提取的一些程序，可直接运行成功。(Wavelet packet feature extraction)

说明：  基于小波变换的图像融合源代码，利用的融合规则分别使用简单的模值取大和基于区域能量。(Image fusion based on wavelet transform source code, the use of fusion rule modulus were obtained using a simple large and region-based energy.)

说明：  带有多种小波基的小波变换程序，可用于图象识别，信号突变检测。(with multiple small Porgy wavelet transform procedures can be used to image recognition, signal mutation detection.)

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

Fast wavelet transforms and numerical algorithms 1

说明：  很详细的hht编程代码，matlab亲测可用，提供了比较清晰的注释，帮助理解(Very detailed HHT programming code, matlab pro test available, provides a relatively clear note to help understand)