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copula_toolbox

于 2011-05-02 发布文件大小:71KB

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下载积分: 1 下载次数: 41

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代码说明：

copula函数主要应用于BB7UgivenV_inverse2(copula function BB7UgivenV_inverse2)

文件列表：

ang_chen1.m,1593,2006-06-04
BB7UgivenV_inverse2.m,1341,2006-06-04
BB7UgivenV_t.m,1243,2006-06-04
bb7_rnd.m,1570,2006-06-04
bisect2.m,2775,2000-11-15
bivarnormcdf.m,1972,2006-03-08
bivarnormcdf2.m,1600,2006-03-08
bivarnormcdf_arg.m,462,2006-03-08
bivartcdfmc.m,2172,2003-08-18
bivartLL.m,551,2001-05-07
bivartpdf.m,1065,2001-08-26
bivnormpdf.m,1118,2007-01-18
bivnorm_tvp1_CL.m,1757,2006-06-04
contents.xls,25088,2011-03-04
contour_plots_code.m,4024,2007-01-18
copula_example_code.m,6937,2008-05-14
corrcoef12.m,832,2002-10-12
cov12.m,559,2001-04-27
empiricalCDF.m,994,2006-02-27
frankCL.m,426,2003-03-11
gumbelCL.m,1095,2006-06-04
GumbelUgivenV_inverse2.m,810,2006-08-22
GumbelUgivenV_t.m,484,2006-06-04
gumbel_cdf.m,1143,2006-06-04
gumbel_pdf.m,1285,2006-06-04
Gumbel_rnd.m,1425,2006-06-04
Gumbel_tvp1_CL.m,1783,2006-06-04
ibm_ccola_rets.txt,85952,2006-02-27
kappa2tau.m,440,2002-05-05
nines.m,1403,2003-04-16
NormalCopula_cdf.m,864,2001-10-15
NormalCopula_CL.m,446,2006-03-09
NormalCopula_pdf.m,730,2001-07-27
plackettCL.m,959,2006-06-04
PlackettUgivenV_inverse2.m,1338,2006-06-04
PlackettUgivenV_t.m,437,2001-08-13
plackett_cdf.m,1324,2006-06-04
plackett_pdf.m,1175,2006-06-04
plackett_rnd.m,1530,2006-06-04
quantiledep.m,767,2006-03-01
readme.txt,1203,2006-06-04
rho2theta.m,517,2002-08-05
sym_jc_cdf.m,1657,2006-06-04
sym_jc_CL.m,1085,2006-06-04
sym_jc_example_code.m,1090,2003-02-13
sym_jc_pdf.m,2639,2006-06-04
sym_jc_rnd.m,2001,2007-08-02
sym_jc_tvp_CL.m,1998,2006-06-04
tau2kappa.m,469,2002-05-22
tCopula.m,1764,2006-06-04
tcopulaCL.m,1390,2006-06-04
tCopula_cdf.m,1898,2006-08-22
tcopula_pdf.m,1569,2006-06-04
theta2rho.m,732,2004-05-16

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多进制相移键控信号的谱相关特性分析原理分析等(M-ary phase shift keying signal spectral correlation analysis theory analysis)

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This is ACE POCS Method use in PAPR reduction

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半监督分类算法
说明：半监督学习(Semi-Supervised Learning，SSL)是模式识别和机器学习领域研究的重点问题，是监督学习与无监督学习相结合的一种学习方法。半监督学习使用大量的未标记数据，以及同时使用标记数据，来进行模式识别工作。当使用半监督学习时，将会要求尽量少的人员来从事工作，同时，又能够带来比较高的准确性，因此，半监督学习目前正越来越受到人们的重视。(Semi-Supervised Learning (SSL) is a key issue in the field of pattern recognition and machine learning. It is a learning method combining supervised learning with unsupervised learning. Semi-supervised learning uses a large number of unlabeled data, as well as labeled data, for pattern recognition. When using semi-supervised learning, it will require as few people as possible to work, and at the same time, it can bring relatively high accuracy. Therefore, semi-supervised learning is receiving more and more attention.)

2021-04-12 11:28:57下载

积分：1

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