work

基于matlab的小波包分解应用于机械振动信号的故障分析(Used in failure analysis of mechanical vibration signals based on the Matlab wavelet packet decomposition)

基于多尺度奇异值分解的图像融合程序及一组待融合图像，以及一篇文献。(Image fusion program based on multiscale singular value decomposition and a set of images to be fused, and a document.)

基于小波变换的心电信号预处理MATLAB源代码(The heart preprocessind based on wavelet transform)

一维小波变换的MATLAB实现方法，包括一维连续小波变换和离散小波变换。(MATLAB in a one-dimensional wavelet transform methods, including the one-dimensional continuous wavelet transform and discrete wavelet transform.)

小波变换，反变换，以及提升小波变换，包括97小波，及53小波(Wavelet transform, inverse transform, as well as the lifting wavelet transform, including the 97 wavelet, and 53 wavelet)

小波变换，小波去噪，包含多种去噪方法，模极大值，自适应，阈值去噪(Wavelet transform, wavelet denoising, including multiple Denoising, modulus maxima, adaptive thresholding)

基于小波变换的ECG信号去噪系统设计,在信号采集时，身体的任一微小运动都会产生“基线漂移”，这是一种低频干扰，同时，由于肌电的存在又产生了高频的肌电噪声，由于空间电磁场的存在又使心电信号中混有50Hz的工频干扰。这些噪声不去除，就会影响下一步的信号处理。 综合运用数字信号处理的理论知识进行生物医学信号增强系统设计，实现ECG信号的去噪，从而加深对小波变换及其应用的理解，建立概念多分辨分析的概念，加深理解信号增强的原理、方法和步骤。本设计的主要内容是设计一个基于小波变换的ECG信号去噪系统，实现ECG信号的去噪。 (ECG signal denoising based on wavelet transform system design, signal acquisition, any small movement of the body will have a " baseline drift" , which is a low-frequency interference, while the high frequency due to the existence of the EMG muscle electrical noise due to the presence of electromagnetic field and the ECG signal mixed with a 50Hz power frequency interference. The noise is not removed, it will affect the next step in the signal processing. Use the theoretical knowledge of digital signal processing for biomedical signal enhancement system design to achieve the de-noising of ECG signal, so as to deepen understanding of the wavelet transform and its applications, to establish the concept of multi-resolution analysis of the concept, deepen the understanding of signal enhancement of the principle, the method and steps. The main elements of this design is the design of an ECG signal denoising based on wavelet transform denoising the ECG signals.)

先进行提升小波变换，然后使用提升小波进行图像的分解和重构(Be carried out on lifting wavelet transform, and then use the images to enhance the wavelet decomposition and reconstruction)

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

图像的5/3小波变换的matlab代码。程序简短，易懂。(Image 5/3 wavelet transform matlab code. Program brief and easy to understand.)