ridge

图象增强小波变换将一幅图象分解为大小、位置与方向都不同的分量。在做逆变换之前能改变小波变换域中某些系数的大小，，这样就能够洋选择的放大所感兴趣的分量而减小不需要的分量。给定一个图象信号，用二维小波分析析对图象进行增强处理。 (Image enhancement wavelet transform decomposition size, location and direction of the different components of an image. Wavelet transform domain, some the size of the coefficient can change before doing the inverse transformation, so can the component of interest to the amplification of the ocean choose to reduce the unwanted weight. Given an image signal, the analysis of two-dimensional wavelet analysis of image enhancement processing.)

本文实现基于贝叶斯(BAYES)阈值的小波(WAVELET)图像去噪算法，相比较其它的小波去噪算法而言，效果非常好(This realization based on Bayesian (BAYES) Threshold the wavelet (WAVELET) image denoising algorithm, compared with other wavelet denoising algorithm, the effect was very good)

PSK信号载波相位符号定时联合估计,载波环采用判决反馈环，去除噪声平方损耗，定时模块采用早迟原理， 里边有详细的注释，希望对大家有用。点击即可运行。(PSK signal carrier phase joint estimation of symbol timing, carrier ring using decision feedback loop, remove the noise square loss, using early-late timing module principle, inside detailed notes, we want to be useful. Click to run.)

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.)

说明：  关于小波变换的一些常用函数，有关多尺度变换，希望可以帮助您(Wavelet commonly used functions, on multi-scale transformation, I hope to help you)

小波变换实现微弱信号检测 BPSK QAM FSK(Wavelet transform weak signal detection BPSK QAM FSK)

wavelet transform to analyze fault for fault location determining

小波变换程序，用于对一维信号，二维信号进行稀疏变换(wavelet transform)

移动窗口二维相关光谱方法matlab的实现，完全是自己参照公式编的哦。。移动窗口二维相关光谱是一种新的二维相关分析方法,它将移动窗口的概念和二维相关分析方法有效地结合在了一起,利用移动窗口将庞大的光谱数据按矩阵分割成若干个便于操作的子矩阵,用二维相关光谱分别处理,将得到的结果综合分析,用以光谱变量和扰动变量为坐标的等高图表现出来,从中可以非常直观地观察出光谱强度在扰动变量方向上的变化,进而找出引起光谱强度突变的特征扰动点。(Moving window two-dimensional correlation spectroscopy method matlab realization, is entirely their own formulas reference the Oh. . Moving window two-dimensional correlation spectroscopy is a new two-dimensional correlation analysis method, it will move the window concept and two-dimensional correlation analysis method is effective to combine together, using the moving window at the huge spectral data matrix is ​ ​ divided into a number of easy to operate a sub-matrix, respectively, using two-dimensional correlation spectroscopy process, comprehensive analysis of the results obtained for the spectral variables, and disturbance variables manifested contour map coordinates, which can visually observe the spectral intensity of the direction of the disturbance variable The change, then find mutations characteristic spectral intensity caused disturbance point.)

EEG signal classification using wavelet feature extraction