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MATLAB数学建模算法教程Mathematical modeling algorithm MATLAB Tutorial(Mathematical modeling algorithm MATLAB Tutorial Mathematical modeling algorithm MATLAB Tutorial)

自适应遗传算法源程序，比较不错的。 具有很大的参考价值(adaptive genetic algorithm source code, the quite good. Great reference value)

本代码是matlab代码，主要是关于典型相关分析方面的，大家可以看看(This code is a matlab code, mainly on the canonical correlation analysis, we can see)

介绍关于如何使用Optisystem Matlab Component(Introduce how to use Optisystem Matlab Component)

是机器学习的例程，构成不同频率的调制信号，有详细的注释，在MATLAB中求图像纹理特征，包括调制，解调，信噪比计算，利用自然梯度算法，可实现对二维数据的聚类，有PMUSIC 校正前和校正后的比较。 ( Machine learning routines, Constituting the modulated signals of different frequencies, There are detailed notes, In the MATLAB image texture feature, Includes the modulation, demodulation, signal to noise ratio calculation, Use of natural gradient algorithm, Can realize the two-dimensional data clustering, A relatively before correction and after correction PMUSIC. )

提出了一种新的基于图像分块重构和线性判别分析相融合的方法，主要用于人脸识别。该方法通过计算两幅图像之间图 像块的重构均值误差，运用线性判别分析求出两幅图像降维后的欧式距离，融合重构误差和欧式距离计算这两幅图像之间的差别 程度。(A new block-based image reconstruction and the integration of linear discriminant analysis method is mainly used for face recognition. This method between the two images by calculating the reconstructed image block average error, calculated using the linear discriminant analysis after dimension reduction of two images Euclidean distance, the integration calculation of reconstruction error and the Euclidean distance difference between these two images level.)

网络控制器的文章，主要应用场合为工控行业，希望对大家有用(Network controller of the article, the main applications for the industrial sector, in the hope that useful)

LSVM : Langrangian Support Vector Machine algorithm LSVM solves a support vector machine problem using an iterative algorithm inspired by an augmented Lagrangian formulation

通过matlab编制程序，对非线性方程组迭代求解。(Through matlab programming, iterative solution of the nonlinear equations)

Scene completion.This is a toy implementation of Scene Completion Using Millions of Photographs for 6.870 Object Recognition and Scene Understanding.(This implementation uses a of 54,000 256x256 images the Oliva lab for which we already have gist-based nearest neighbors data. )