29-12-12

基于小波变换的图像去噪 基于小波变换的图像去噪基于小波变换的图像去噪基于小波变换的图像去噪(fegfegrhthtjtfhdrggsg)

本程序采用显示方案实现“平均曲率运动(MCM)”模型(realize the MCM model)

Informed Search techniques

无线传感器网络虚拟力仿真算法，有算法效果图，可以下下来看看。(Wireless sensor network virtual force simulation algorithm, the algorithm effect chart, you can look at the next.)

一种改进的自适应滤波器的状态估计，效果非常之好,是用MATLAB编写的，直接在matlab下运行就可以看到完美的滤波效果，自适应算法是sage—husa算法，较传统的滤波器有很大提高(An improved adaptive filter state estimates, the effect is very good, is written in MATLAB, directly in matlab running, you can see a perfect filtering effect, the adaptive algorithm is sage-husa algorithm, than the traditional filtering has greatly improved)

这些都是通信系统仿真与分析一书的源代码，希望对初学者有用，从基本的理论很好的用matlab进行了最基本的仿真(These are the communications system simulation and analysis of the source code of the book, I hope useful for beginners, from the basic theory of good use to the most basic matlab simulation)

说明：  Modify the Matlab Gauss Elimination routine given in lectures so that it (a) performs implicit complete pivoting, and (b) handles m right hand sides at once by performing an LU decomposition of the matrix A first and then doing forward substitution and back substitution (hence not modifying the right hand side as the elimination is perfomed). Test your program and then run it on the system AX = B(Modify the Matlab Gauss Elimination routine given in lectures so that it (a) performs implicit complete pivoting, and (b) handles m right hand sides at once by performing an LU decomposition of the matrix A first and then doing forward substitution and back substitution ( hence not modifying the right hand side as the elimination is perfomed). Test your program and then run it on the system AX = B)

MINIMUM SHIFT KEYING WAVEFORM IN MATLAB

瑞利分布＋杂波雷达信号MATLAB仿真程序源码，希望望对有做雷达信号的朋友有帮助 可直接使用。 已通过测试。 (Rayleigh distribution+ hybrid radar signal MATLAB simulation program source code, I hope to look on the friend of a radar signal to help can be used directly. Has been tested.)

基于QR分解的岭回归函数，这个函数是非的有用是已经证明过的准确程序( center input and output, so we can estimate w0 separately since we don t want to shrink w0 )