ctrllab30-control-system-toolbox

模式识别的一部分，用于确定二值边界的，不错的算法额(Part of a pattern recognition algorithm for binary boundary determined )

C语言编的简单遗传算法程序 各项功能齐全(SGA-simple Genetic Algorithm)

说明：  参考维基百科（https://en.wikipedia.org/wiki/Variance-based_sensitivity_analysis）的取样过程以及对应的Estimators。理论性的东西就不进行复述了，这里主要阐述用MATLAB（R2018b）对某个特定函数进行Solo indices敏感性分析的过程。大致可分为四个过程：采样，构建函数，函数输出（将样本带入函数得到输出值），计算Sobol指数（估算一阶影响指数和全局影响指数）(Sobol global sensitivity analysis)

说明：  参考模型为三阶的模型参考自适应控制，设计自适应率，跟踪效果很好。 原创。 (Model reference adaptive control)

TRACKING SMALL TARGET IN INFRAREAD SEQUENCE IMAGE USING KALMAN FILTER

说明：  简单介绍了鲁棒控制的例子，以及练习时代码，仅供参考 。(This paper briefly introduces the example of robust control and the code of practice.)

针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷 入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。 该方法考虑了图像中像素点灰度􀀂 􀀂 􀀂 邻域灰度均值对作为阈值对图像进行分割 利用混沌运 动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜 索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索 时间, 提高了收敛率。(Calculation of its large capacity and particle swarm algorithm is easy to fall to strike the best threshold for the two-dimensional entropy image segmentation method Into the local optimum and slower, the proposed two-dimensional entropy image segmentation method based on chaotic particle swarm optimization algorithm. The method takes into account the image pixel the gray 􀀂 􀀂 􀀂 neighborhood average gray value as a threshold for image segmentation chaotic transport Dynamic randomness, ergodicity and initial value sensitivity of chaotic particle swarm optimization algorithm with the threshold method in two-dimensional space for the global search On request. Experimental results show that the entropy method of image segmentation method based on chaotic particle swarm optimization algorithm for threshold optimization to reduce the search Time and improve the convergence rate.)

A matlab code to compute heat conduction

对花卉的数据集分别通过“五折法”、随机产生训练样本、欧式平方距离、绝对值距离、契比雪夫距离和马氏距离进行数据集的识别。(Data sets, respectively, for flowers through the " half of Law" , randomly generated training samples, European squared distance, absolute distance, Chebyshev distance and Mahalanobis distance for data set identification.)

说明：  一套非常漂亮的图片站源码，以前本人用过的，而且排名很好！(A very beautiful picture station source code, before I used, but a very good position!)