DYNIC-OF-MATLAB

把mat文件 转换成 hdr格式文件。可用SPM调用。(Put into a mat file hdr files. SPM can be used to call.)

递归式最小均方（RLS）算法的基本思想是力图使在每个时刻对所有已输入信号而言重估的平方误差的加权和最小，这使得RLS算法对非平稳信号的适应性要好。与LMS算法相比，RLS算法采用时间平均，因此，所得出的最优滤波器依赖于用于计算平均值的样本数，而LMS（NLMS）算法是基于集平均而设计的，因此稳定环境下LMS（NLMS）算法在不同计算条件下的结果是一致的(Recursive least-mean-square (RLS) algorithm for the basic idea is to try to make in every moment of all the input signal in terms of re-evaluation of the weighted squared error and the smallest, which allows non-stationary RLS algorithm for adaptive signal better. Compared with the LMS algorithm, RLS algorithm uses the average time, therefore, the resulting optimal filter depends on the used to calculate the average number of samples, and the LMS (NLMS) algorithm is designed based on set average, and therefore a stable environment LMS (NLMS) algorithm in different conditions, the results of the calculation is consistent)

说明：  测试网络的容错性,并且对实际含噪声的字母进行识别，以实现BP网络的识别功能。(Test network fault tolerance, and the actual identification of letters with noise, to achieve the BP network, recognition.)

program for lms.it is the lms algorithm for bpsk modulated sound wave

induction motor graph simulation

用MATLAB实现gold序列的子函数，可在主函数中调用，生成2^n-1长度的gold序列。(use MATLAB to make out gold sequence，which obtained 2^n-1 data.)

ADMM 交替方向乘子法Alternating Direction Method of Multipliers(Alternating Direction Method of Multipliers)

matlab实现的灰度处理方法，是一篇很好的文献(matlab realize the gray-scale approach is a good literature)

一个关于Matlab数学工具软件实例简明教程的电子文档(A mathematical tool Matlab instances on Concise Guide to the Electronic Document)

利用夹角余弦距离进行样本数据分类。实现步骤主要分为以下两部分：a、待测样品X与训练集里每个样品Xi的距离采用夹角余弦距离公式计算。b、循环计算待测样品和训练集中各已知样品之间的距离，找出距离待测样品最近的已知样品，该已知样品的类别就是待测样品的类别。(Using the sample data classification Angle cosine distance.Implementation steps are divided into the following two parts: a, sample under test with each of the samples in the training set X Xi distance using the included Angle cosine distance formula.B, loop calculation under test samples and the distance between the known samples training focus, find out the known closest to the sample under test samples, the samples of known category is the category of the sample under test.)