dwt

NormThresh of wavelet coefficient

Harr小波具有紧支撑、零调和性和优良的正交性等优点，因此选择它作为小波变换的基函数。对采样数据进行4层小波包变换得到16维的特征样本。(Harr wavelet has compact support, zero reconcile and excellent orthogonality, etc., so choose it as the base function of wavelet transform. 4 layers of sampled data wavelet packet transform feature samples 16 dimensions.)

这是采用小波变换以及压缩感知的理论编写的图像融合程序(This is the wavelet transform and the theory of compressed sensing image fusion program written in)

小波变换在故障诊断中的应用 441 18.1 引言 441 18.2 基本原理 442 18.3 小波变换在轴承故障诊断中的应用 444 18.3.1 轴承外环故障诊断 444 18.3.2 轴承滚动体故障诊断 448 18.4 小波变换在齿轮故障诊断中的应用 450 18.5 小波包在轴承故障诊断中的应用 452 18.5.1 轴承外环故障诊断 453 18.5.2 轴承滚动体故障诊断 454(wavelet transform fault diagnosis of Introduction 441 18.1 441 18.2 442 basic tenets 18.3 wavelet transform bearing fault diagnosis of 444 18.3.1 ring bearing 444 1 Fault Diagnosis 8.3.2 rolling bearings Fault Diagnosis 448 18.4 wavelet transform in Gear Fault Diagnosis of 450 1 8.5 wavelet packet bearing fault in the diagnosis of 452 18.5.1 ring bearing fault diagnosis 453 18. 5.2 roller bearings Fault Diagnosis 454)

基于Matlab的JPEG2000图像压缩实现，离散小波变换DWT，程序中图片的位置修改下可以自己运行程序看到效果(Matlab-based implementation of the JPEG2000 image compression, discrete wavelet transform DWT, where the image changes the program may be run its own program to see results)

小波变换、EMD以及EMD结合小波变换，几种常用的时频去噪方法在脑电预处理中运用的的对比分析，算法过程解释详细，有利于初学者入门学习；小波变换、EMD以及EMD结合小波变换，几种常用的时频去噪方法在脑电预处理中运用的的对比分析，算法过程解释详细，有利于初学者入门学习

用matlab编程实现了ridgelet多尺度变换，实现了图像的解析，重构，压缩等功能(Ridgelet with matlab programming a multi-scale transformation to achieve the image resolution, reconstruction, compression and other functions)

小波变换、小波逆变换代码，数字信号处理领域常用(Wavelet transform, wavelet inverse transform code, digital signal processing used)

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.)

利用小波提升算法实现了第二代小波变换,将之应用在信号去噪中,实现了数据的边界对称延拓,去噪效果较好.(Wavelet Lifting algorithm using the second generation wavelet transform, to be used in signal de-noising, the realization of the data symmetric boundary extension, denoising better.)