电力线噪声模型仿真

用Hausdorff距离对两角点集进行配准，得到点集间的仿射变换，从而实现图像的自动配准。此算法以角点作为Hausdorff距离的配准特征，与直接选用边缘来配准的方法相比较，大大减小计算量。(Hausdorff distance on the corners with a point set registration, be affine transformation between sets in order to achieve automatic image registration. This algorithm is based corner as the Hausdorff distance matching characteristics, and use Edge to direct registration method of comparison, greatly reduced computation.)

The following Matlab project contains the source code and Matlab examples used for orthogonal least squares algorithms for sparse signal reconstruction. Added after previous version ols_gp: Sparse reconstruction by Orthogonal Least Squares followed by Gradient Pursuit ols_nomp: Sparse reconstruction by Orthogonal Least Squares followed by Approximate Conjugate Gradient Pursuit ols_pcgp: Sparse reconstruction by Orthogonal Least Squares followed by Partial Conjugate Gradient Pursuit The source code and files included in this project are listed in the project files section, please make sure whether the listed source code meet your needs there.

matlab gui电子期刊，适合初学者(matlab gui electronic periodicals )

对流扩散方程的上风差分，又称为迎风差分。时间项为显性差分。(Convection diffusion equations with upwind difference, also known as the upwind difference. Time for the explicit finite difference. )

用matlab实现动画的制作，三维、二维制图，图像处理。。。。(Animation, drawing. . .)

人工蜂群算法 matlab 实现，人工蜂群算法源代码(Artificial bee colony algorithm matlab implementation)

回声隐藏利用人耳听觉系统的时域掩蔽特性，在载体数据的环境特性中嵌入水印信息(Echo hiding ear hearing system of time domain masking properties, environmental characteristics of the data in the carrier embedded watermark )

用matlab求股票的var、cvar，含数据处理直至计算结果。使用矩阵方法，注释较多，适合入门学习(using matlab for finance modeling:this is for coputing var,cvar for stocks. Using a matrix method, suitable for beginners to learn)

以下是均方误差、峰值信噪比以及熵的程序代码在MATLAB 中的实现(The following is the realization of the mean square error, peak signal to noise ratio and entropy code in MATLAB)

说明：  在matlab环境下，实现小波变换对信号处理方面的试验。(In the matlab environment, the realization of wavelet transform for signal processing experiments.)