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it is a ieee paper on fact devices used for ower flow controller

五点差分求解椭圆型方程边值问题，方便快捷，简单好用(five points)

模式识别课程中的主成分分析方法PCA的matlab实现源码(Pattern Recognition in the principal component analysis PCA matlab to achieve source)

有循环检测，周期性检测，针对EMD方法的不足,光纤陀螺输出误差的allan方差分析。( There are cycle detection, periodic testing, For lack of EMD, allan FOG output error variance analysis.)

说明：  标准微粒群算法，采用matlab编程实例。(Standard particle swarm optimization using matlab programming examples.)

说明：  通过最大熵和自适应灰度阈值方法来对图像进行分割，可得到效果较好的分割图像(By maximum entropy and the adaptive threshold method of image segmentation, image segmentation can be obtained better)

自适应最小均方算法滤波代码，源信号为窄带信号，对源信号加随机噪声，通过自适应滤波器得出输出信号(matlab/LMS/)

CONVEX_HULL is a MATLAB library which reads a file containing the coordinates of a set of points in 2D, computes the convex hull of the points, and displays it.

This code computing unicriterion net flow scores in PROMETHEE II in matlab programming.

MIDACO是一般的优化问题求解器。 MIDACO可应用于连续（NLP），离散/整数（IP）和混合整数（MINLP）的问题。问题可能被限制在平等和/或不等式约束。 MIDACO适合多达数百至几千优化变量的问题。 MIDACO实现了一个自由衍生物，启发式算法的处理方法处理的问题，因为黑盒可含有关键功能特性，如非凸性，不连续或随机噪声。(MIDACO is a solver for general optimization problems. MIDACO can be applied to continuous (NLP), discrete/integer (IP) and mixed integer (MINLP) problems. Problems may be restricted to equality and/or inequality constraints. MIDACO is suitable for problems with up to several hundreds to some thousands of optimization variables. MIDACO implements a derivative-free, heuristic algorithm that treats the problem as black-box which may contain critical function properties such as non-convexity, discontinuities or stochastic noise.)