OFDMmatlab

matlab教材附带的代码 可以运行.关于通信方面的仿真。(the matlab code about communitinication)

QPSK for AWGN and Rayleign fading channel example

matlab编程指南电子版，很值钱的呦，关于matlab写程序的方法(matlab electronic programming guide, it is valuable Yo)

说明：  迎着早晨的朝阳龙求凤长长的伸了一下懒腰,突然闻到一股香风向他袭来,闻着这熟悉的香味,知道这是他心爱的师柔身上的发出的迷人香味，转过身去将心爱的人儿紧紧地搂在怀里，"柔儿，怎么这么早就起来了，你的身体刚刚才好，应该多多休息一下。"(Demand facing the morning sun dragon phoenix long stretched a bit lazy waist, suddenly, he smelt a fragrant wind hit, smell the familiar fragrance, know that this is his favorite teacher charming issued soft body scent, turned to a loved one child tightly in his arms, &quot Rou Er, how so early up, just go about your body, it should be lot of rest.&quot )

光纤信道盲均衡CMA算法，MATLAB开发环境，比较通用的一种算法(Fibre Channel CMA blind equalization algorithms, MATLAB development environment, more generic algorithm)

风力机模型MATLAB仿真，叶尖速比，转矩，利用系数的MATLAB仿真，SIMULINK搭建仿真模型(MATLAB simulation of wind turbine model, the tip speed ratio, torque, utilization factor of MATLAB simulation, SIMULINK simulation model building)

通信过程的MATLAB建模，过程清晰，分析到位，感觉不错(MATLAB modeling the communication process, process definition, analysis in place, feeling good)

详细的说明了如何使用该数学软件，很容易学！(Detailed instructions on how to use the mathematical software, it is easy to learn )

EM277.zip是圣西门子S200的编程软件v4.0 Step 7 MicroWin的库(EM277.zip St. Simons S200 programming software v4.0 Step 7 MicroWin library)

实现聚类K均值算法： K均值算法：给定类的个数K，将n个对象分到K个类中去，使得类内对象之间的相似性最大，而类之间的相似性最小。 缺点：产生类的大小相差不会很大，对于脏数据很敏感。 改进的算法：k—medoids 方法。这儿选取一个对象叫做mediod来代替上面的中心 的作用，这样的一个medoid就标识了这个类。步骤： 1，任意选取K个对象作为medoids（O1,O2,…Oi…Ok）。 以下是循环的： 2，将余下的对象分到各个类中去（根据与medoid最相近的原则）； 3，对于每个类（Oi）中，顺序选取一个Or，计算用Or代替Oi后的消耗—E（Or）。选择E最小的那个Or来代替Oi。这样K个medoids就改变了，下面就再转到2。 4，这样循环直到K个medoids固定下来。 这种算法对于脏数据和异常数据不敏感，但计算量显然要比K均值要大，一般只适合小数据量。(achieving K-mean clustering algorithms : K-means algorithm : given the number of Class K, n will be assigned to target K to 000 category, making target category of the similarity between the largest category of the similarity between the smallest. Disadvantages : class size have no great difference for dirty data is very sensitive. Improved algorithms : k-medoids methods. Here a selection of objects called mediod to replace the center of the above, the logo on a medoid this category. Steps : 1, arbitrary selection of objects as K medoids (O1, O2, Ok ... ... Oi). Following is a cycle : 2, the remaining targets assigned to each category (in accordance with the closest medoid principle); 3, for each category (Oi), the order of selection of a Or, calculated Oi Or replace the consumption-E (Or))