PCA

基本的S变换matlab实现 用于时频分析 为初学者提供基本代码(S transformation for time-frequency analysis to provide basic code for beginners)

余弦变换-DCT。好用的小波变换方法程序。(Cosine transform-DCT. Use of wavelet transform.)

理解有源滤波器的工作原理、性能特点。学习有源滤波器的设计方法。(Understand the working principle of active filter performance characteristics. Learning active filter design methods.)

基于MATLAB的简易声音信号频谱分析仪设计源码及设计报告。可以实现音频信号的不同频段滤波。(MATLAB simple voice signal spectrum analyzer design source code and design reports. Can achieve a filtering of the different frequency bands of the audio signal.)

复杂杂波背景下，海面红外图像中舰船目标检测的关键是如何降低虚警、检测出真正的 目标。为了实现这个目标，首先利用Haar小波函数进行小波变换，对图像进行预处理；然后进行恒 虚警检测（CFAR）；第三步采用行程法对检测的目标进行标记；最后采用管道滤波法剔出虚假目标， 检测出真正的目标。经仿真实验证明，此方法能有效地降低虚警，在复杂杂波背景中检测出目标。 (The key of ship detection in sea infrared image with complex clutter background is how to reduce false alarms and detect true targets.In order to achieve this aim,a novel algorithm is proposed. First,Haar wavelet transform technology is used as preprocessing,then constant false alarm rate(CFAR) detetion,then run-length label to mark objects detected by the above step,finally pipeline filter to reduce false alarms and detect true targets.Experiment results indicate that this method can effectively reduce false alarms and detect true targets in complicated sea background. )

对图像做二维离散小波变换，分解级数为3级，并重构图像，不直接调用Matlab的dwt和idwt函数。(pair of 2-dimensional images DWT, decomposition of the three series, and Image Reconstruction, not directly call Matlab dwt and idwt function.)

bandelet denoising toolbox for matlab

通过设计Visual C程序源码对简单易懂的一维信号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波与Haar小波变换，从而的到小波分解系数；再通过改变分解的到的各层高频系数数进行信号的小波重构达到消噪噪的目的。在这一程序源码实现的过程中能直观地理解信号小波分解重构的过程与在信号消噪中的重要作用，和在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。 可直接 (Design Visual C program source code on a simple one-dimensional signal with a Gaussian white noise Daubechies wavelet, Morlet wavelet and Haar wavelet transform, and thus to the wavelet coefficients and then change the decomposition to each storey wavelet reconstruction frequency coefficient of the number of signal to noise canceling noise. In the process of realization of this program source code can be intuitively understood the signal wavelet decomposition and reconstruction process and an important role in signal denoising, and the selection coefficient in the high frequency coefficients of the layers of the weight of processing noise cancellation signal impact. Can be directly)

音频数字水印技术，采用小波变换，psnr、snr、nc等参数计算(Audio watermarking, DWT translation,parameter caculation)

说明：  基于PCA的遥感图像融合，效果不错。可以作为遥感图像融合方面入门学习使用。(PCA-based remote sensing image fusion, good results. Integration of remote sensing images can be used as an introduction to use.)