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matlab-study-material

于 2012-08-08 发布 文件大小:281KB
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  matlab简明教程,有大量实例,供大家参考学习!(matlab simple tutorial, a large number of instances, for your reference to learn!)

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  • mohucjunzhi
    此方法用模糊聚类的方法对全体样本进行分类,称为模糊c均值(Fuzzy c-means)
    2012-04-20 10:07:46下载
    积分:1
  • emd
    用于采用HHT方法处理地震波等信号,生成固有模式函数EMD的Matlab源程序(the EMD program of HHT method in analyzing wave)
    2014-08-29 19:07:29下载
    积分:1
  • scfde
    lte中上行链路scofdm调制方式的实现过程,包括dft,idft和ofdm过程(lte uplink scofdm modulation implementation process, including the dft, idft and ofdm process)
    2012-12-04 13:56:46下载
    积分:1
  • DCTbasedwatermark
    基于dct的图像水印实现,用MATLAB哟(watermark based on DCT)
    2009-04-20 16:33:02下载
    积分:1
  • mexcdf.R14sp1-2.r2811
    matlab的netcdf插件安装程序,适用于R14版本(Matlab netcdf plug-in installation procedures, apply to R14 version )
    2012-04-30 20:42:05下载
    积分:1
  • one
    MATLAB File for receiver design
    2013-11-29 15:21:54下载
    积分:1
  • VSI_03Level
    Three level pulse converter is VSI converter used to convert the DC voltage to AC voltage using Sin Pulse Width Modulation technique.
    2012-01-23 20:49:20下载
    积分:1
  • SALINI
    LTE-A . AN OVERVIEW AND CHALLENGES
    2013-12-23 23:19:43下载
    积分:1
  • BLDC
    基于matlab的无刷直流电机仿真速度PI,电流PI双闭环仿真(Matlab-based simulation of brushless DC motor, using speed PI, current PI double closed loop control.)
    2021-04-18 13:48:51下载
    积分:1
  • matlab
    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.)
    2014-02-18 09:59:02下载
    积分:1
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