dwt

基于matlab的小波变换程序，可以方便的进行信号的小波分析。经过验证，可以使用。这里使用的是morlet小波。主要是处理地震数据。(Matlab-based wavelet transform process, you can easily carry out the wavelet analysis of signals. After verification, you can use. Here use morlet wavelet. Processing seismic data.)

本书简明扼要地介绍了时间序列及其相关领域的基本概念和基本理论，对ARMA序列预测、时间序列的统计分析、时间序列的时频分析和时间序列的小波变换等给出了有关分析计算方法，结合MATLAB编程应用，介绍了MATLAB时间序列分析有关函数的功能和用法，阐述了如何利用这些函数解决工程应用中的问题。(This book succinctly describes the time sequence and its related fields of basic concepts and theories of the ARMA series forecasting, time series statistical analysis, time series analysis and time-frequency wavelet transform of time series analysis and calculation are given about methods, combined with MATLAB programming applications, the introduction of time series analysis MATLAB functions about functions and usage, explains how to use these functions to solve engineering problems in the application.)

这是一本介绍旋转机械故障诊断的论文，采用小波变换方法提取故障特诊，我导师的一个项目就是用的这种特征提取方法，比较成功。(this is a book that introduce the matheds of error dector and we have tested it in our project.)

基于小波变换的包络分析用于轴承故障诊断的源代码(Bearing envelope analysis)

一个提升小波变换的matlab工具包。可以实现97，53，haar等系列的提升小波分解与重构。(an upgrade wavelet transform Matlab tool kit. 97,53 can be achieved, haar series of lifting wavelet decomposition and reconstruction.)

使用四元数小波变换图像流估计。是对“Coherent Multiscale Image Processing using Dual-Tree Quaternion Wavelets”的实现。代码很详细。(Use quaternion wavelet transform image flow estimation. Is the " Coherent Multiscale Image Processing using Dual-Tree Quaternion Wavelets" implementation. Code is very detailed.)

一个基于小波阈值的信号处理程序，通过自适应阈值方式抑制信号噪声(A threshold based on wavelet signal processing procedures, through the adaptive threshold signal noise suppression methods)

一个基于小波变换的数据聚类样例 Matlab实现(A sample Matlab based on wavelet transform data clustering)

小波基矩阵乘法快速算法工具箱，里面有目录，供大家学习参考！(Tools for Fast Matrix Multiplication in Wavelet Basis)

说明：  给出了在matlab环境下的源代码，经过了上机调试，可以实现小波变换对图像的二次压缩！(given Matlab environment in the source code, after the Machine, can achieve a wavelet transform of the second image compression!)