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利用matlab编写的vibe算法，处理速度比较慢，但对于学习了解vibe的原理有一定的帮助(Vibe algorithm by using matlab, processing speed is slow, but to learn the principle of vibe has certain help)

用于分类的主判别变量算法(principal discriminant variate algorithm) ( principal discriminant variate algorithm for two classes, x1 and x2. x1 is the training samples in the 1st class with each column being the spectrum characterizing the corresponding sample. x2 is the training samples in the 2nd class with each column being the spectrum characterizing the corresponding sample. lamda is the penalty weight defining the balance between FLDA and PCA. dvnum is the number of principal discriminant variates to be computed. A defaul value for dvnum is 2. dv is the principal discriminant variates. scores is the matrix with each row being the scores of the samples on the corresponding principal discriminant variate. xmean is the mean spectra of the sample, which was used for mean-centering the data in training and prediction. )

单纯形法，求解线性规划问题的通用方法。这里给出其Matlab源程序(Simplex method for solving linear programming problems common method. Here are its Matlab source)

3G系统中，利用扩频技术来扩频的代码。即为PN码产生器的程序代码。(The code of PN generate for spread spectrum tecnology.)

程序名称:gm21.m GM(2,1)模型 程序功能:利用GM(2,1)模型进行预测。 程序编写:mongvi@126.com 开发指导:刘思峰教授 程序发布:南京航空航天大学灰色系统研究所(Program name: GM gm21.m (2,1) model Program function: using GM (2,1) model to predict. Programming: mongvi@126.com Development direction: Professor Liu Sifeng)

说明：  模拟退火算法应用于光学模拟方向的程序代码(Simulated annealing algorithm is applied to the direction of the optical simulation code)

有限元分析作业源码, piecewise单元,积分 高斯近似算法两种，并计算最小势能(Finite Element Analysis Operating source, piecewise unit, integral Gaussian approximation algorithm for two, and calculation of minimum potential energy)

aircarft stability with adaptive controller

说明：  异步电机的直接转矩控制，可以实现圆形磁链控制，绝对不坑你(The direct torque control of the asynchronous motor can realize the circular flux control, which will never hurt you)

In factor analysis rotations of the loadings are very often applied, whereas in chemometrics these methods are very seldom used. This is in spite of the fact that it is possible to obtain better conditions for interpretation of PCA models on complex data. I here provide an algorithm by which it is possible to apply rotations from the Orthomax family (quartimax and varimax) to a PCA-model.