data_fft

说明：  基于建筑抗震设计规范的反应谱（地震影响系数曲线）(Response Spectrum based on anti-seismic code for buildings)

matlab 神经网络算法应用于图片中人物性格识别,通过对神经网络的训练，可以识别图像中是男性还是女性。。。(matlab neural network algorithm is applied to the picture of character recognition, neural network through training, can identify the image is male or female. . .)

说明：  莱斯利人口预测模型 莱斯利矩阵为91阶方针表示从0岁到90岁各个年龄段的生育率和存活率集合(leslie )

这是自己用MATLAB写的角点检测源程序，非常简单，效果良好(This is written using MATLAB corner detection source, very simple and effective)

简单但是很全的polar码，编码和译码matlab代码。(Simple but very wide polar code, coding and decoding matlab code.)

这是关于matlab语言学习的经验，其中包括两个txt文档很方便下载，可以在手机上看，写的很好，值得看看。(This is about the matlab language learning experience, including two txt documents easy to download, you can phone point of view, well written, it is worth a look.)

Particle swarm optimization

2d PhC calculation bandgap by PWE method

此为模式识别中的Fisher线性判别方法求分类器。进行了男、女错误率和总错误率的统计。 全部程序流程如下： 1、读取FAMALE.TXT文件把身高或体重给数组，并求x1的样本均值m1和内离散度S1； 2、读取MALE.TXT文件把身高或体重给数组，并求x2的样本均值m2和内离散度S2； 3、求最佳变换向量和阀值点； 4、读取Test2.txt文件把对应的身高或体重给数组A并求A的样本数M； 5、把最佳变换向量和阀值点、x代入判别方程g（x）； 6、对本判别的错误率进行统计。(This is the pattern recognition method, to calculate the Fisher linear discriminant classifier .Were male , female and total error rate error rate statistics . All program flow is as follows : 1 , read FAMALE.TXT file to height or weight to the array, and find the sample mean m1 x1 and internal dispersion S1 2 , read MALE.TXT file to height or weight to the array, and find the sample mean m2 and x2 within the dispersion S2 3 , for the best transformation vector and the threshold point 4 , read Test2.txt file to the corresponding height or weight requirements for the array A and A is the number of samples M 5 , the best transformation vector and the threshold point , x substituted into the discriminant equation g (x) 6 , determine the error rate of the statistics . )

主成分分析的matlab源程序，用以标准化数据，精简指标，减少指标之间信息的重叠。(Principal component analysis matlab source for standardized data, streamline indicators, reduce duplication of information between indicators)