比较全面的alpha稳定分布的matlab程序

打开Matlab，输入代码，执行，得结果(Open Matlab, input code, the implementation of the findings)

wave packet propagation in one dimension

完成一个二进制FSK通信系统的Monte Carlo仿真，检测器用平方率检测器。(the matlab source code of FSK)

iris recognition using matlab p-file

zigag算法，将1-N^2的数字按照“Z”路径排序。附有程序运行截图。(zigzag algorithm)

永磁同步电机系统的滑模观测器设计，非常实用，算法很先进(Sliding model observer based Permanent Magnet Synchronous Motor)

Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules: If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)

几乎涵盖了光学各种仿真的学位论文，值得大家去深入学习。matlab的使用会进一步加深。(Almost covers the optical simulation of the dissertation, worth to study further. The use of matlab will further deepen.)

说明：  对于全方位的识别和优化做了很详细的分析程序处理和样本对照(For the full identification and optimization of doing a very detailed analysis of the samples were processed and)

说明：  仿真锁相环 及锁相环的MATLAB代码(pll MATLAB )