Y500642

This is a collection of m-files I created to complete a research project into the DC components of various encoding techniques. Eight of the files create random bit sequences that conform to their coding requirements. The others were files I found useful in the scope of the project and supplement the generating m-files. (This is a collection of m-files I created to complete a research project into the DC components of various encoding techniques. Eight of the files create random bit sequences that conform to their coding requirements. The others were files I found useful in the scope of the project and supplement the generating m-files.)

It is a program for State Feedback H Controller design for continuous time system based lmi approach.

说明：  利用D-S证据理论进行数据融合，应用场景为无线传感器网络目标定位，决策级融合(DS evidence theory data fusion, wireless sensor network application scenarios targeting, decision level fusion)

matlab提供使用的全部函数说明和范例指导。全面而便于查询(matlab provides all the functions used in the guidance notes and examples. A comprehensive and easily accessible)

说明：  基于MATLAB-Simulink的系统仿真技术与应用,该书全面的讲述了利用Matlab进行系统仿真技术，具有很强的是实用性。(MATLAB-Simulink)

对生成的随机序列进行自相关（平衡性）进行测试。(Autocorrelation test )

MATLAB绘制地形地图时可以使用的地图绘制程序！(Mapping program can use MATLAB topographic map!)

飞秒泵浦半导体激光器速率方程，简化的四能级系统(rate equation of laser power by f-laser)

一些关于数据车牌识别的资料，对你进行车牌的识别程序设计有用(Some information about the data license plate recognition, license plate recognition program is useful for the design)

In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle s position and velocity. Each particle s movement is influenced by its local best known position but, is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.