wave-move

小波包分解包括重构信号问题程序，这是一个matlab程序，经过测试可用，数据采用自己的数据。(Including the reconstructed signal wavelet packet decomposition problem program, which is a matlab program, tested available data using their own data.)

Second generation wavelets and applications

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及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。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)

各种小波包函数的matlab 实现,对理解小波包很有用处(Various wavelet packet function of matlab, is very useful to understand the wavelet packet )

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)

对图像做二维离散小波变换，分解级数为3级，并重构图像，不直接调用Matlab的dwt和idwt函数。(pair of 2-dimensional images DWT, decomposition of the three series, and Image Reconstruction, not directly call Matlab dwt and idwt function.)

自己写的小波图像压缩，包括普通压缩和序列图像压缩(himself wrote of wavelet image compression, including the compression and ordinary sequence Image Compression)

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)

包含压缩传感的随机矩阵程序，如小波变换和高斯随机矩阵和omp重构算法(Random matrix containing the compressed sensing programs, such as wavelet transform and Gaussian random matrices and omp reconstruction algorithm)

关于小波变换的降噪处理，包括强制降噪，给定阈值降噪，默认阈值降噪等，并给出了对比图(Noise reduction processing on the wavelet transform, including mandatory noise reduction, noise reduction given threshold, default threshold noise reduction, and gives comparison chart)