beamshape

这个程序是基于小波变换的信号奇异性检测及去噪 的一些例程(using wavelet method and SVD to process the signal and denoise)

说明：  可以将目标矩阵进行线性褶积运算，用于数字信号处理(The target matrix can be linearly convoluted for digital signal processing)

说明：   这是一个用小波神经网络进行非线性函数逼近的例子，拟合效果非常好，保证能运行！有详细注释！我是参考《青岛海洋大学学报》 2001年第1期 一种基于BP算法学习的小波神经网络编写的，大家可以针对原文更好的理解我的程序！(This is a wavelet neural network with nonlinear function approximation example of fitting results is very good, guaranteed to run! Detailed Notes! I refer to Journal of Ocean University of Qingdao，2001 ，“a learning algorithm based on BP wavelet neural network ”, you will understand me better for program!)

用于产生各种多小波滤波器系数的程序，包括Cl2小波，GHM多小波等等，很好用(Used to produce a variety of multi-wavelet filter coefficients procedures, including Cl2 wavelet, GHM multiwavelet and so on, very good use)

有关小波包分解和介绍的PPT，适合于初学者快速掌握小波包分解相关问题。(the PPT of wavelet packet decomposition and the introduction , suitable for beginners to quickly master the wavelet packet decomposition.)

美国著名Rice大学的小波变换工具箱，非常实用，实现了几乎所有常用的小波变换功能。(prominent American Rice University wavelet transform Toolbox, very practical, to achieve almost all commonly used wavelet transform function.)

matlab编的瑞利面波的正演模拟，用于浅层地震勘探研究(Matlab compiled Rayleigh wave in the forward modeling of, used in the shallow seismic exploration and research )

单分量仿真信号进行小波变换后，小波脊线的提取(After the simulation of a single component signal wavelet transform, wavelet ridge extraction)

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

一个图像小波数字水印的matlab代码,利用小波变换，在DC分量上实现自适应编码(An image digital watermarking wavelet matlab code, the use of wavelet transform, the DC component on the realization of adaptive coding)