MditonglvboA

genetic_algorithm optimized matlab program_population

模糊PID控制程序，这是毕业设计学生做的，可运行。(Immune genetic algorithm source code, which is a hybrid intelligent algorithm, good resources.)

受控自回归滑动平均模型的梯度迭代算法，经过多次迭代计算之后，能够有效的逼近真实值(Controlled autoregressive moving average model of gradient iterative algorithm, after several iterations, can effectively approach the true value)

单纯形法matlab程序，计算方程组（函数的个数显然大于方程个数）(Matlab program of the simplex method, the calculation equations (function number is clearly greater than the equation number))

matlab环境下的低通滤波设计及实现，我也不是很懂(matlab environment of low-pass filter design and realize, I do not很懂)

mimo and siso capacity

利用小波分析对污染信号消噪以恢复原始信号(Using wavelet analysis of contamination signal to recover the original signal de-noising)

matlab中fspecial函数的C++实现(Matlab implementation of fspecial function in C++ )

聚类算法，不是分类算法。分类算法是给一个数据，然后判断这个数据属于已分好的类中的具体哪一类。聚类算法是给一大堆原始数据，然后通过算法将其中具有相似特征的数据聚为一类。这里的k-means聚类，是事先给出原始数据所含的类数，然后将含有相似特征的数据聚为一个类中。所有资料中还是Andrew Ng介绍的明白。首先给出原始数据{x1,x2,...,xn}，这些数据没有被标记的。初始化k个随机数据u1,u2,...,uk。这些xn和uk都是向量。根据下面两个公式迭代就能求出最终所有的u,这些u就是最终所有类的中心位置。(Clustering algorithm, not a classification algorithm. Classification algorithm is to give a figure, and then determine the data belonging to a specific class of good which category. Clustering algorithm is to give a lot of raw data, and then through the algorithm which has similar characteristics data together as a class. Here k-means clustering, is given in advance the number of classes contained in the raw data, then the data contain similar characteristics together as a class. All information presented in or Andrew Ng understand. Firstly, raw data {x1, x2, ..., xn}, the data is not labeled. K random initialization data u1, u2, ..., uk. These are the vectors xn and uk. According to the following two formulas can be obtained final iteration all u, u is the ultimate all these classes the center position.)

OFDM仿真原始代码。基于matlab实现OFDM的全过程。压缩文件中包含7个文件。(OFDM code files, include the whole procedure of OFDM. there are seven files in this package.)