OptimMatlab

mppt for photovoltaic systme

此实验是关于详细的采样定理，有设计与实现及MATLAB程序代码。(It is useful.)

matlab与vc混和编成(Matlab and the mixture into vc)

simulink环境下的永磁同步电机的磁场定向控制，采用id=0的控制策略(simulink environment of permanent magnet synchronous motor field oriented control, using id = 0 control strategy)

说明：  遗传算法优化,经过matlab R2011b 测试可用(GA example.Untitle.m in the package is the main program)

LDPC编译码的matlab仿真。内涵源程序以及文章说明，希望对大家有所帮助(LDPC codec matlab simulation. Source and content of the article shows, we want to help)

基于矩量法仿真的笼形天线宽带化设计 (Method of Moments simulation cage antenna design is based on broadband)

利用kalman滤波算法对状态空间描述的位移测量系统进行了滤波处理，对系统输出的真实位移、测量位移和滤波位移进行了对比，显示了kalman滤波算法较好的滤波性能。(Displacement measurement system described by the equation of states were filtered by Kalman filter algorithm. The output of the system, including the real displacement, measuring displacement and filtering displacement were compared, and the results showed the great performance of Kalman filter algorithm.)

这个是短时傅立叶变换程序,希望对大家有用了!(This is a short-time Fourier transform procedures in the hope that it may be useful right!)

In 1960, R.E. Kalman published his famous paper describing a recursive solution to the discretedata linear filtering problem [Kalman60]. Since that time, due in large part to advances in digital computing, the Kalman filter has been the subject of extensive research and application, particularly in the area of autonomous or assisted navigation. A very “friendly” introduction to the general idea of the Kalman filter can be found in Chapter 1 of [Maybeck79], while a more complete introductory discussion can be found in [Sorenson70], which also contains some interesting historical narrative.(In 1960, R. E. Kalman published his famous paper describ ing a recursive solution to the discretedata li near filtering problem [Kalman60]. Since that time, due in large part to advances in digital computi Vi, the Kalman filter has been the subject of extens ive research and application. particularly in the area of autonomous or assis ted navigation. A very "friendly" introductio n to the general idea of the Kalman filter can be f ound in Chapter 1 of [Maybeck79] while a more complete introductory discussion can be found in [Sorenson70] which also contains some interesting historic al narrative.)