RD

这是之前上传的Extract_test_IMFCC程序里面调用的子函数，作配合使用，请看清楚再下载(This is one subfunction of Extract_test_IMFCC uploaded before.Since pudn.com cannot upload several functions, they must divided.)

nordig channel simulation

2005BCI竞赛数据3 详细的BCI竞赛数据(2005BCI BCI Competition Data 3 detailed race data)

MATLAB Code for Notch Filter Design and finding peak power of signal.

QPSK 的星座图仿真 有仿真信噪比为0dB，10dB，20dB的时候的星座图。(QPSK constellation diagram simulation the simulation signal-to-noise ratio of 0dB, 10dB, 20dB when the constellation diagram.)

说明：  配电网潮流计算，前推回代法，matlab程序(distribution system calculation)

三相电源的MTALAB仿真，对于初学三相电的人，可以通过仿真直观的感受三相电波形分配(Three-phase power MTALAB simulation, three-phase power for the beginner who can intuitively feel the simulation waveform of three-phase power distribution)

matlab源程序 很有用的 你们可以试用一下(matlab source code useful you can try)

用MATCOM实现VC_对MATLAB中_m文件的调用(With MATCOM achieve VC_ on file in MATLAB call _m)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(（Evolu2tionary Algorithm - EA）。PSO 算法属于进化算法的一种，和遗传算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years ((Evolu2tionary Algorithm- EA) .PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting random solutions, through iterative search for the optimal solution, which is also uated by the quality of the fitness solution, but it is much simpler than genetic algorithms rule, it does not have the genetic algorithm cross (Crossover) and variant (Mutation) operation, which by following the current search to find the optimal value to the global optimum. the algorithm for its easy implementation, high accuracy, and fast convergence advantages attracted academic attention, and in solving practical problems demonstrated its superiority.)