gp11

使用直接模拟蒙特卡罗法的Matlab编程，里面三个算例，如湖面积、资产路径等的概率求解法～(Vincent Leclercq, The MathWorks, 2007 vincent.leclercq@mathworks.fr Ths is the set of files (with the powerpoint presentation, in french or in english) used for the Webinar "Simulation de Monte Carlo en MATLAB". - The first demo (LakeArea, run MainLakeArea) is computing the size of a polyogon using a MC approach - The second demo (PortSim, run WebinarScript) can do 2 things: First, we genrate some equity paths, to verify the lognormality If changing the mode to OptionPricing (uncomment one of the first line), then those spaths will be used for pricing an asian option - the 3rd Demo,in myMC (run MonteCarlo.m) , show how to simulate some corelated asset paths - The 4th demo, (run VanillaPricingUsingDifferentMethods.m in the VarReduction folder) , wil compare th results obtrtain byt differents reduction of Variance technics or "quasi" 礛ont Carlo simultion using Hamlton and sobol Sequences)

基于最大信噪比的盲源分离算法（附参考文章），能够分离线性混合的超高斯和亚高斯源信号, 并且可以有效地分离语音信号。((With reference to the article), can be separated and super-Gaussian linear mixed sub-Gaussian source signal to noise ratio based on the largest blind source separation algorithm, and can effectively separate the voice signal.)

new algorithm for estimation in every field of science for matlab implementation mostly

一本很好学习神经网络和其MATLAB实现的书籍.(A very good study MATLAB neural network and its implementation books.)

Provides segmentation introducing clusters for each region

数字图像处理空间维纳滤波LSWF模型MATLAB代码(Digital image processing space Wiener filter LSWF model MATLAB code)

说明：  这是基于吴和黄的的研究进而得到"percenta"的方法(This is used to obtain the "percenta" line based on Wu and Huang)

player mega32 music play

分枝定界法程序，解混合整数线性规划《详解MATLAB在最优化计算中的应用》中的分枝定界法程序，稍作了修改(Branch and bound method procedures, the solution mixed integer linear programming, " Detailed MATLAB optimization calculation in the application" in the branch and bound procedure, slightly modified)

SVD point matching .I write it by myself .and it can work in matlab.but the result is not well