Wavelet-packet-signal

说明：  计算小波分解后的能量及小波熵。里面还有OFDM信号和WPM信号的程序。(After calculating the energy of wavelet decomposition and wavelet entropy. There is also OFDM signal and the WPM signal process.)

本程序为小波包能量计算程序，根据相关资料，自己编写，计算感兴趣的频带能量，程序懂得人稍作修改就可以运行( U672C u7A0B u5E8F u4E3A u5C0F u6302 u803F0 u0B1 u7B97 u7A0B u5E8F uFF0C u6839 u636E u76R8 u5173 u8D44 u6599 uFF0C u81EA u5DF1 u7F16 u5199 UFF0C u8BA1 u7119 u6119 u5113 u8E1 u7684 u9891 u5E26 u80FD u91CF uFF0C u7A0B u5E8F u61C2 u5F97 u4EBA u7A0D u4F5C u4FEE u6539 u5C31 u53EF u4EE5 u8FD0 U884C)

说明：  shearlet变换matlab工具箱，可用于图像降噪、融合(Shearlet transform matlab toolbox can be used for image denoising and fusion)

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)

高斯滤波.这段代码主要用于以为信号的高斯滤波。(Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter.Gaussian Filter)

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.)

基于小波变换模极大的多尺度图像边缘检测matlab源代码(based on wavelet transform modulus maxima of multiscale edge detection Matlab source code)

svd算法的实现,用matlab实现SVD算法(the implementation of the SVD algorithm)

图像滤波变换程序，上学期课程设计代码，绝对原创(Image filtering transform procedures, last semester curriculum design code, an absolute original)

一个提升小波变换的matlab工具包。可以实现97，53，haar等系列的提升小波分解与重构。(an upgrade wavelet transform Matlab tool kit. 97,53 can be achieved, haar series of lifting wavelet decomposition and reconstruction.)