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免疫遗传算法解决TSP问题的源程序，属于本人写文章测试benchmark problem用的程序。(Immune genetic algorithm to solve TSP problem source, which I write the test procedures used benchmark problem.)

说明：  ieee distribution test feeder

1. 基于simulink搭建一个QPSK发送链路，QPSK调制信号经过了瑞利衰落信道，观察信号经过衰落前后的星座图，观察信道特性。仿真参数：信源比特速率为500kbps，多径相对时延为[0 4e-06 8e-06 1.2e-05]秒，相对平均功率为[0 -3 -6 -9]dB，最大多普勒频移为200Hz。(1. Based on simulink structures, QPSK sent a link, the Rayleigh fading channel after the QPSK modulation signal, were observed before and after signal after the decline of constellation diagram, observation channel characteristic. Simulation parameters: the source is 500 KBPS bit rate, relative multipath time delay of [0 8 e 4 e- 06-06 e-05] 1.2 seconds, the relative average power is [0-3-6-9] dB, most of the doppler frequency shift is 200 hz.)

非常好的三相整流与逆变控制，适合广大初学者学习(Very good three-phase rectifier and inverter control, suitable to the beginners to learn )

在GM-MIMO集群建立基于地理位置。GM-MIMO图论应用于找到一个最佳的转发路径。(In GM-MIMO cluster is established based on geographic location. GM-MIMO graph theory applied to find the best path forward.)

Multi-class Coding (adapted from from LS-SVM for SPIDER). Encode (code_MOC, code_ECOC, code_OneVsAll, code_OneVsOns) and decode (codedist_hamming, codedist_bay) a multi-class classification task into multiple binary classifiers.

说明：  这是一个矩阵变换器双空间矢量控制的Matlab仿真程序，有simulink和s函数，用M语言编程。是作为电力行业的研究仿真(This is a matrix converter double-space vector control, Matlab simulation program, with simulink and s functions, with the M-language programming. As a simulation of the power industry)

使用viterbi方法译码的源代码，可以绘制最佳路径选择过程的仿真图(Viterbi decoding method using the source code, you can draw the best path selection process simulation diagram)

GrTheory - Graph Theory Toolbox. Functions: grBase - find all bases of digraph grCoBase - find all contrabases of digraph grCoCycleBasis - find all independent cut-sets for a connected graph grColEdge - solve the color problem for graph edges grColVer - solve the color problem for graph vertexes grComp - find all components of graph

说明：  智能微电网粒子群优化算法,微源：光伏、风机、发电机、储能等((Smart Microgrid GA, micro sources: photovoltaic, wind turbines, generators, energy storage, etc.))