duffing

计算股票的历史波动率的MATLAB函数:securityVolatility.m(security Volatility, securityVolatility.m)

协同通信信道保密容量与功率分配因子的关系matlab仿真程序(secrecy capacity for cooperative communication)

A viable particle swarm optimization to update algorithm, MATLAB code to run correctly simulation, ease of use

matlab关于kalman的源代码。很全，值得看看学习一下……(good)

this is simple sample of ART neural network: main file: ART.m

Test file for reg. Please run the other files.

脉冲压缩雷达信号处理 脉冲压缩性能分析 海明窗加权(failed to translate)

（压缩包里一共有5个代码） pca+lda+粗糙集+模糊神经网络 saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat 1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat 2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat 3.将disdata组成决策表(savers.m)，通过对disdata的条件属性进行约简，得到其一个约简，组成新的测试集rstest和训练集rsstudy存为imagersdata.mat 4.对rsstudy进行模糊神经网络训练(savecul.m)，对模糊神经网络的参数进行调整学习将其存入culdata.mat 5.用runfnn.m对rstest进行测试得到其识别率 savem.m和cm.m是用最小距离分类器对训练集和测试集进行分类.(pca+ lda+ Rough Set+ fuzzy neural network saveORLimage.m will ORL face database is divided into test set and training set ptest for pstudy keep imagedata.mat Treasury will face 1.savelda.m first dimensionality reduction pca, lda used feature extraction, a new test set and training set ldatest for ldastudy keep imageldadata.mat 2. Ldastudy carried out on the discretization (discretimage.m), to be discrete matrix of disdata, deposited to imagedisdata.mat 3. Disdata the composition of the decision table (savers.m), the conditions on the attributes disdata about Jane, has been one of its reduction to form the new test set and training set rstest for rsstudy keep imagersdata.mat 4. Rsstudy training fuzzy neural network (savecul.m), on the parameters of fuzzy neural network to learn to adjust their deposit culdata.mat 5. Rstest used to test for runfnn.m by its recognition rate cm.m is savem.m and minimum distance classifier on the training set and test set classificati)

自动控制方面的MATLAB程序，PID控制(Automatic control of MATLAB, PID control)

这是用来解常微分方程的原代码，是我自己编的哦。(This is the solution of ordinary differential equations for the original code, is a series of my own Oh.)