Matlabprogram

说明：  本源程序为matlab文件，实现最小生成树和关键路径的查找。(the source document for Matlab and achieve minimum spanning tree and find the critical path.)

遗传算法程序，运行环境为MATLAB，可移植性非常好。程序本身不存在错误。(Genetic algorithms program, run the environment for MATLAB, portability is very good. Process itself does not exist error.)

use a three order loop to track the GPS L2C signal, could be useful for beginner

说明：  internal function involving the removal of ramdom noise

阵列信号处理中的其中一个传统子空间方法仿真程序，二维music算法。(One of the traditional subspace method simulation program in array signal processing, the two-dimensional music algorithm.)

本代码是容量限制交通分配的代码。但是不通过完整的OD表进行配流，而是针对组成OD表的逐一起始点、终点的基础数据进行配流。路权是取的BFR函数，加了距离惩罚函数。(This code is the capacity limit traffic assignment code. But not through the complete OD table assignment, but for each table consisting OD initial, end with the underlying data stream. Right of way is to take the BFR functions, plus a distance penalty function.)

This simulation demonstrates the running of a DC motor with controlled (thyristor) line rectification (5 hp 240V 1200 rpm) rated torque Tr = 30 N.m.Results of out current and speed of the dc motor can be observed together with the rectifier voltage

In this paper, we show how support vector machine (SVM) can be employed as a powerful tool for $k$-nearest neighbor (kNN) classifier. A novel multi-class dimensionality reduction approach, Discriminant Analysis via Support Vectors (SVDA), is introduced by using the SVM. The kernel mapping idea is used to derive the non-linear version, Kernel Discriminant via Support Vectors (SVKD). In SVDA, only support vectors are involved to obtain the transformation matrix. Thus, the computational complexity can be greatly reduced for kernel based feature extraction. Experiments carried out on several standard databases show a clear improvement on LDA-based recognition

本段程序主要实现了两个源的特征束的形成代码编程与波束形成图的演示(Eigenbeams for two sources)

隔离准Z源逆变器的开环控制，希望对初学者有些帮助。(Isolation the open-loop control of Z source inverter, and want some help for beginners. )