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ldpcBP
说明: LDPC码的BP算法译码MATLAB程序(LDPC decoding algorithm BP MATLAB)
- 2006-04-26 09:50:53下载
- 积分:1
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FXLMS_MA_differ_mu
FXLMS算法在有源噪声控制的应用,初级通道给定8位的权矢量,次级通道给定传递函数,不同步长进行比较(different comparison in FXLMS)
- 2014-11-13 22:07:48下载
- 积分:1
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channel_estimation
基于MATLAB的doa估计的信道估计模型仿真,(Based on MATLAB doa estimated channel estimation model simulation,)
- 2015-10-28 16:50:55下载
- 积分:1
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bkqshiaz
关联规则挖掘算法的matlab程序,我编写了Apriori算法的LTgqvz 步骤,可以自动生成关联规则,计算支持度、置信度以及 WJFlqaT 检测,很好的小程序。(Association rule mining algorithm matlab program, I wrote LTgqvz step Apriori algorithm can automatically generate association rules, computing support, confidence and WJFlqaT detection, good little program.)
- 2016-01-21 22:27:19下载
- 积分:1
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feature-selection-master
最小冗余最大相关性(MRMR)(MRMR.M)
需要外部库。详情请见MRMR。下载一个更新版本的互信息工具箱
偏最小二乘(PLS)回归系数(ReGCOEF.m)
使用MATLAB统计工具箱中的PLSReress
ReliefF(分类)和RReliefF(回归)(ReleFracePr.M.)
从Matlab STATS工具箱中包装Releff.m。这是Matlab R2010B以后提供的。
ReliefF的另一个选择是使用ASU特征选择工具箱中的代码。这使用WEKA工具箱的ReleFEF,因此需要额外的库。请参阅相应的文档。
费雪评分(Fisher评分)
围绕ASFS特征选择工具箱围绕FSFisher。M(Minimum Redundancy Maximum Relevance (mRMR) (mRMR.m)
Needs external library. See mRMR.m for details.
Download a newer version of the mutual information toolbox
Partial Least Squares (PLS) regression coefficients (regCoef.m)
Uses plsregress.m from MATLAB statistics toolbox
ReliefF (classification) and RReliefF (regression) (relieffWrapper.m)
Wraps around relieff.m from the MATLAB stats toolbox. This is available MATLAB r2010b onwards.
Another option for ReliefF is to use the code from ASU Feature Selection toolbox. This uses ReliefF from weka toolbox and hence needs additional libraries. Please see the corresponding documentation.
Fisher Score (fisherScore.m)
Wraps around fsFisher.m from the ASU Feature Selection toolbox)
- 2020-07-22 09:48:44下载
- 积分:1
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VCMATLAB
如何用VC6.0和MATLAB进行联合编程文章(How to conduct a joint program VC6.0 and MATLAB article)
- 2009-11-19 21:30:54下载
- 积分:1
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disteu
DISTEU Function
DISTEU Pairwise Euclidean distances between columns of two matrices
Input:
x, y: Two matrices whose each column is an a vector data.
Output:
d: Element d(i,j) will be the Euclidean distance between two
column vectors X(:,i) and Y(:,j)
Note:
The Euclidean distance D between two vectors X and Y is:
D = sum((x-y).^2).^0.5
- 2013-03-15 15:11:01下载
- 积分:1
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matrix-iteration-method
matlab中用矩阵迭代法求解问题的C程序(matrix iteration method)
- 2011-10-23 10:34:35下载
- 积分:1
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pso
PSO theory explanation
- 2013-10-03 18:03:19下载
- 积分:1
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pls
create a gaussian bell
- 2009-10-22 13:23:13下载
- 积分:1