wavelet

根据小波变换和噪声信号地能量分布特性，提出了一种先用小波变换对含噪图像进行多尺度分解，求出各尺度小波变换高频系数地噪声方差和阈值，利用各尺度地阈值对高频系数进行处理，然后利用小波变换系数重构图像，实现图像降噪地方法。(According to wavelet transform and noise signal and energy distribution characteristics, a first wavelet transform of the noisy image multiscale decomposition, obtained the high-frequency-scale wavelet transform coefficients and noise variance and thresholds, using the scale to the threshold value of the deal with high-frequency coefficients, and then the use of wavelet transform coefficients reconstructed image, to realize image denoising methods.)

利用小波包变换对信号进行分解及重构，对于初学者是一个很好的学习材料。(Wavelet packet transform signal decomposition and reconstruction, is a good learning materials for beginners.)

基于小波变换的语音识别，内含毕业论文和摘要以及可执行源程序(Speech recognition based on wavelet transform, containing thesis and summary of executable source code)

基于小波变换的信号检测和去噪的matlab源程序 基于小波变换的信号检测和去噪的matlab源程序(Matlab source of the signal detection and denoising based on wavelet transform)

matlab程序，X-CT图像处理，用小波分解去除噪声(matlab program, X-CT image processing, noise removal by wavelet decomposition)

一种基于EMD分解后对imf分量利用小波分解进行去噪的方法，给出了相应的例子，有注释(Based on the EMD decomposition after the imf component by using the method of wavelet decomposition denoising, corresponding examples are given, with comments)

谐波小波包分解程序，并且将其应用于声发射信号特征提取(Harmonic wavelet packet decomposition procedure, and will be applied to acoustic emission signal feature extraction)

说明：  提出了一种基于复解析小波变换的相位诊断齿轮故障的方法。复解析小波变换将Hilbert变换与小波分析紧密结合在一起,具有自适应分析能力。利用复解析小波变换得到齿轮振动信号的相位,其功率谱图上可提取调制边频带结构来识别故障模式。试验结果表明这种方法可有效应用于齿轮局部故障诊断中。(A new method using the phase based on complex analytical wavelet transform for fault diagnosis of gears was proposed. The phase of vibration signals of gears is got by complex analytical wavelet transform, which combines Hilbert transform with wavelet transform tightly and possesses adaptive analysis ability. By making spectrum analysis of the phase, the sideband structure in power spectrum can be protruded, and the fault pattern can be identified. Experimental results show that the proposed method is effective in local defect detection of gears.)

双树复小波，比小波变换更加优秀的多尺度变换，具有更好地方向选择性。包含去噪应用(Dual tree complex wavelet transform, multiscale better than wavelet transform, has better selectivity. A denoising method include.)

本人自己编写的小波变换脊提取程序，可用与信号分析．欢迎指导．(I have written wavelet transform ridge extraction procedures, can be used with the signal analysis. Welcomed the guidance.)