wavelet

利用小波分析原理对某信号进行分解与重构，并可提取指定层数上的高、低频信号。(A signal is decomposed and reconstructed by using wavelet analysis principle, and high and low frequency signals can be extracted from the specified number of layers.)

说明：  压缩包中为小波变换的程序，可在MATLAB 中使用，可进行时频分析(The compression package is a wavelet transform program, which can be used in MATLAB and can be used for time-frequency analysis)

说明：  53小波提升的编解码代码，可用于图像的53小波变换(53)

双树复小波程序，具有平移不变心，改进了小波变换(The DTCWT program with shift-invariant heart improve wavelet transform)

OFDM系统完整程序，小波/小波包变换在OFDM中的应用的程序。(Complete program of the OFDM system, wavelet/wavelet packet transform in OFDM applications program.)

一种用于尿沉渣图片的分割方法，先用小波变换和形态学，再使用边缘检测和阈值分割(urine for a picture segmentation method, use wavelet transform and morphology, re-use of edge detection and thresholding segmentation)

M. N. Do的经典的关于轮廓波变换的matlab代码，里面有matlab代码、论文、测试图片，很齐全，是很好的学习资料！(The MN Do classic on contourlet transform matlab code matlab code, papers, test image there, very complete, good learning materials.)

这是一款用来分析心率变异性的matlab程序，有线性分析和非线性分析，包含输出结果包含频谱分布、统计学描述、样本熵、小波分析(This is a matlab program used to analyze heart rate variability, linear analysis and nonlinear analysis contains the output contains spectral distribution, statistical description sample entropy, wavelet analysis)

基于多小波变换的医学图像融合方法研究基于多小波变换的医学图像融合方法研究(Based on Multi-Wavelet Transform Method for Medical Image Fusion Based on Multi-Wavelet Transform Medical Image Fusion Method)

循环平稳信号是一类特殊的非平稳信号，其统计特征具有随时间呈周期变化的特点。旋转机械由于周期运行方式其振动信号具有循环平稳特性，因此利用循环平稳分析方法能够提取出在平稳假设下所不能得到的隐藏故障特征信息，为有效地分离和识别旋转机械早期微弱故障特征提供可能。(The cyclostationary signal is a special type of non-stationary signal whose statistical characteristics have a periodic variation with time. Due to the cyclical operation of the rotating machinery, the vibration signal has the characteristics of cyclostationary stability. Therefore, the cyclostationary analysis method can extract the hidden fault feature information that can not be obtained under the stationary assumption, which provides the possibility to effectively separate and identify the early weak fault features of the rotating machinery.)