nonlinear dynamics

使用DCT和小波变换的数字音频水印生成/解码程序，可存活于方差0.05的高斯白噪声及不同程度的剪切。内含程序/测试文件介绍。(Digital wartermarking encoding/decoding program with DCT and wavelet transform. nice robustness against Gaussian noise with variance less than 0.05 and any type of cropping attack. functions/test files introduction included)

这是一个轴承故障分解程序，给予小波变换，小波去噪，小波重构与EMD相结合，有时频谱，边际谱，功率谱(This is a to bearing failure decomposition program given wavelet transform, wavelet denoising wavelet reconstruction combined with EMD, sometimes the spectrum, marginal spectrum, power spectrum)

利用小波变换，通过设置阈值对图像进行去噪。 首先对图像用小波进行2层分解，然后通过设置硬阈值和软阈值的方法，对图像高频部分去噪。(The wavelet transform is used to denoise the image by setting threshold. Firstly, the image is decomposed into 2 layers by wavelet, and then the high frequency part of the image is denoised by setting the hard threshold and the soft threshold.)

Rice大学的ricewavelet小波变换工具包，用于matlab环境下，内含图像处理所需的几乎所有小波变换功能，很好很强大(failed to translate)

用迭代法生成haar子程序上 以及信息隐藏的详细功能、包含内容说明(Iterative method to generate a the haar subroutine and information hidden features, including content description)

dual tree complex wavelet transform

MATLAB实现小波变换经典程序，包括采用多孔trous算法实现小波变换、基于小波消噪的雷达回波检测、小波插值与小波构造、小波滤波器构造和消噪程序、小波谱分析mallat算法经典程序、小波图像重构 Matlab 程序等等(MATLAB wavelet transform classic program, including the use of undecimated wavelet transform algorithm to achieve the wavelet transform, the radar echo detection based on wavelet denoising, wavelet interpolation and wavelet construction, construction and de-noising of the wavelet filter program, a small spectral analysis mallatclassic algorithm procedures, wavelet image reconstruction Matlab programalgorithm)

一种小波分解，用于多分辨率分解，在分解的过程中，同时给出各级的细节和概貌。(a trous wavelet decomposition)

在 MATLAB 中的窗函数,十分简单： 矩形窗 三角窗 汉宁窗 海明窗 布拉克曼窗 恺撒窗 (In MATLAB, the window function is very simple: a rectangular window of triangular windows Hanning Hamming Blackman Window Caesar Window)

小波变换模极大值重建信号的matlab源程序，来源于胡广书的《现代信号处理教程》附属光盘(Wavelet transform modulus maxima reconstruction signal matlab source code, derived from HU-book " modern signal processing tutorial subsidiary Disc)