-
21912914pca
一个关于人脸识别的pca主程序分析算法的matlab程序(About the pca a face recognition algorithm matlab main program analysis procedures)
- 2009-04-07 23:09:14下载
- 积分：1
-
fenpei
分配问题的实现,是利用匈牙利算法实现的MATLAB代码！(The realization of the distribution is the use of the MATLAB code Hungarian algorithm!)
- 2010-05-14 14:31:23下载
- 积分：1
-
SHEPWM_2lvl_3ph_7ang
说明： 通过对比两电平，五电平，我们设计一种7电平切换，得到更平滑切换(By comparing two levels and five levels, we design a kind of 7-level switching to get smoother switching)
- 2020-06-30 18:00:34下载
- 积分：1
-
suanshubianma
MATALAB的算术编码应用(Application of Arithmetic Coding MATALAB)
- 2007-12-11 10:25:07下载
- 积分：1
-
study-antena-by-mom
半波阵子天线的矩量法研究，很好的材料，详细介绍了半波阵子天线运用矩量法的计算的步骤，和积分方程(Stream of half-wave antennas method of moments, very good material, details the stream of half-wave antenna using moment method of calculation steps, and the integral equation)
- 2011-04-26 17:05:35下载
- 积分：1
-
Poisson_CG
CG法解Poisson方程，通过迭代输出结果并画图，结果包含迭代步数以及无穷范数(Solution of Poisson equation by CG method, iterative output results and drawing, the result contains iteration step number and infinite norm)
- 2020-06-29 20:20:02下载
- 积分：1
-
LTE_PHY_PSSGen
This generates a PSS sequence in LTE downlink.
This can be used as a test vector reference for cell search procedure
- 2011-12-18 21:01:47下载
- 积分：1
-
Simulation
All optical discrete Fourier transform processor for 100Gbps OFDM
- 2013-12-28 12:53:11下载
- 积分：1
-
matlab22
说明： 有用的MATLAB 数字图像处理说明 有兴趣看看(MATLAB useful digital image processing that will look with interest at)
- 2009-08-01 17:14:08下载
- 积分：1
-
NewK-means-clustering-algorithm
说明： 珍藏版，可实现，新K均值聚类算法，分为如下几个步骤：
一、初始化聚类中心
1、根据具体问题，凭经验从样本集中选出C个比较合适的样本作为初始聚类中心。
2、用前C个样本作为初始聚类中心。
3、将全部样本随机地分成C类，计算每类的样本均值，将样本均值作为初始聚类中心。
二、初始聚类
1、按就近原则将样本归入各聚类中心所代表的类中。
2、取一样本，将其归入与其最近的聚类中心的那一类中，重新计算样本均值，更新聚类中心。然后取下一样本，重复操作，直至所有样本归入相应类中。
三、判断聚类是否合理
采用误差平方和准则函数判断聚类是否合理，不合理则修改分类。循环进行判断、修改直至达到算法终止条件。(NewK-means clustering algorithm ，Divided into the following several steps:
A, initialize clustering center
1, according to the specific problems, from samples with experience selected C a more appropriate focus the sample as the initial clustering center.
2, with former C a sample as the initial clustering center.
3, will all samples randomly divided into C, calculate the sample mean, each the sample mean as the initial clustering center.
Second, initial clustering
1, according to the sample into the nearest principle clustering center represents the class.
2, as this, take the its recent as clustering center of that category, recount the sample mean, update clustering center. And then taking off, as this, repeated operation until all samples into the corresponding class.
Three, judge clustering is reasonable
Adopt error squares principles function cluster analysis.after clustering whether reasonable, no reasonable criterion revisio)
- 2011-04-06 20:45:56下载
- 积分：1
