sime-kpca

用于机械原理课程中对RRR结构的运动分析，可用于计算位移、速度、加速度(Courses for mechanical principle of the movement structure of the RRR analysis, can be used to calculate the displacement, velocity, acceleration)

经典谱分析和改进算法，用于估计信号功率谱和方位，(Classical spectral analysis and improved algorithms for estimating the signal power spectrum and the position,)

对人类poly（A）位点的特征提取函数，共可提取K-mer、eiip、Z-curse、pwm、热力学结构等374项特征(On the characteristics of human poly (A) sites extraction function of extractable K-mer, eiip, Z-curse, pwm, the thermodynamic characteristics of structure 374)

svm工具箱，可以很好进行分类，并附有实例，可以很直接的看出分类效果(svm toolbox, well classification, with examples, can direct that the classification results)

说明：  matlab实现的数字水印，经验证能够实现(matlab implementation of digital watermarking, proven to achieve)

matlab 的基本操作书籍，对初学matlab很有用，很值得推荐(The basic operation matlab books, matlab very useful for beginners, it is worth recommending)

暂时只支持jpeg2000支持的 cdf97 和spline53 可以这样来测试： x=imread( E:studyjpeg2000imageslena.tif ) ％ see the decomposition coefficients y=wavelift(x, 1, spl53 ) using spline 5/3 wavelet figure subplot(1,2,1) imshow(x) subplot(1,2,2) imshow(mat2gray(y)) ％ see the reconstruction precision yy=wavelift(x, 5) using cdf 9/7 wavelet ix=wavelift(yy,-5) inverse sum(sum((double(x)-ix).^2)) (only temporary support jpeg2000 support cdf97 and spline53 this can be measured Examination : x = imread (E : study jpeg2000 images lena.tif)% see the d ecomposition coefficients wavelift y = (x, 1, spl53) using spline 5/3 wavelet figure subplot (1,2,1) imshow (x) subplot (1,2, 2) imshow (mat2gray (y))% see the reconstructi on precision wavelift yy = (x, 5) using cdf 9/7 wavelet ix = wavelift (yy.-5) inverse sum (sum ((double (x)- ix). ^ 2)

crross over and fittnes GA unit commitment

严格按照BP网络计算公式来设计的一个matlab程序,对BP网络进行了优化设计 优化1：设计了yyy，即在o(k)计算公式时，当网络进入平坦区时(<0.0001)学习率加大， 出来后学习率又还原 优化2：v(i,j)=v(i,j)+deltv(i,j)+a*dv(i,j) (A Matlab procedures in strict accordance with the BP network computing formula to design, the optimization design was carried out on BP network Optimization design of 1: YYY, that is O (k) in the formula, when the network into the flat area (<0.0001) learning rate increase, after learning rate and reduction Optimization of 2:v (I, J) =v (I, J)+deltv (I, J)+a*dv (I, J) )

m-fsk modulation and de modulation