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GFS Toolbox

于 2021-04-10 发布
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代码说明：

说明：  二型模糊系统的工具箱，一个很好学习二型模糊的软件(Toolbox for Type 2 Fuzzy Systems, a good software for learning Type 2 Fuzzy Systems)

文件列表：

GFS Toolbox, 0 , 2019-03-17
GFS Toolbox\AFZ.fig, 3613 , 2008-06-11
GFS Toolbox\AFZ.m, 1564 , 2008-06-11
GFS Toolbox\defuz.m, 1199 , 2008-07-01
GFS Toolbox\Docs, 0 , 2019-03-17
GFS Toolbox\Docs\Compare.docx, 12994 , 2008-08-14
GFS Toolbox\Docs\Comparison.docx, 20924 , 2008-08-14
GFS Toolbox\Docs\GFS Vs FIS.ppt, 483328 , 2008-06-13
GFS Toolbox\Docs\IT2 Snaps.doc, 185856 , 2008-06-27
GFS Toolbox\Docs\Records.m, 1331 , 2008-08-04
GFS Toolbox\Docs\SYS.docx, 12188 , 2008-08-18
GFS Toolbox\Docs\Till 30.06.08.ppt, 629760 , 2008-06-30
GFS Toolbox\Docs\Tutorial proposal 03.doc, 97280 , 2008-08-26
GFS Toolbox\Docs\Tutorial Proposal for GECCO 2009 (Beowulf Clusters for Evolutionary Computing).pdf, 86575 , 2008-08-21
GFS Toolbox\Docs\Tutorial proposal.docx, 57970 , 2008-08-25
GFS Toolbox\Docs\Tutorials.doc, 432640 , 2008-05-30
GFS Toolbox\ENDT2.fig, 33306 , 2008-06-02
GFS Toolbox\ENDT2.m, 7003 , 2008-06-02
GFS Toolbox\Exp.fis, 732 , 2009-03-23
GFS Toolbox\FIS Examples, 0 , 2019-03-17
GFS Toolbox\FIS Examples\Examp.fis, 734 , 2008-11-09
GFS Toolbox\FIS Examples\Examp2.fis, 828 , 2008-06-18
GFS Toolbox\FIS Examples\ImpIRIS8.fis, 713 , 2008-08-02
GFS Toolbox\fis2gfs.m, 3785 , 2008-11-09
GFS Toolbox\FUZ.fig, 25463 , 2008-11-16
GFS Toolbox\FUZ.m, 231988 , 2009-03-23
GFS Toolbox\Gen1.GFS, 1403 , 2008-11-14
GFS Toolbox\GFS Examples, 0 , 2019-03-17
GFS Toolbox\GFS Examples\Examp.GFS, 935 , 2008-11-09
GFS Toolbox\GFS Examples\iris.GFS, 1281 , 2008-10-22
GFS Toolbox\GFS Examples\IRISIT2.GFS, 1122 , 2008-08-02
GFS Toolbox\GFS Examples\IRISIT2-1.GFS, 1132 , 2008-09-03
GFS Toolbox\GFS Examples\IRISIT2-2.GFS, 1133 , 2008-09-03
GFS Toolbox\GFS Examples\IRISIT2-3.GFS, 1128 , 2008-09-03
GFS Toolbox\GFS Examples\IRISIT2-4.GFS, 1134 , 2008-09-03
GFS Toolbox\GFS Examples\IRISST1.GFS, 927 , 2008-08-03
GFS Toolbox\GFS Examples\IRISTT21.GFS, 1317 , 2008-08-03
GFS Toolbox\GFS Examples\IRISTT21-1.GFS, 1326 , 2008-08-03
GFS Toolbox\GFS Examples\IRISTT21-2.GFS, 1324 , 2008-08-04
GFS Toolbox\GFS Examples\IRISTT21-3.GFS, 1324 , 2008-08-12
GFS Toolbox\GFS Examples\Test GT21.GFS, 1608 , 2008-11-01
GFS Toolbox\GFS Examples\Test ST1.GFS, 1384 , 2008-08-28
GFS Toolbox\GFS Examples\Test TT21.GFS, 1706 , 2008-11-01
GFS Toolbox\GFS Examples\Test TT22.GFS, 1523 , 2009-03-23
GFS Toolbox\GFS Examples\Test TT23.GFS, 1788 , 2008-11-02
GFS Toolbox\GFS Validation Experiments, 0 , 2019-03-17
GFS Toolbox\GFS Validation Experiments\All&T.fig, 36357 , 2008-07-22
GFS Toolbox\GFS Validation Experiments\All&T1.jpg, 60365 , 2008-07-22
GFS Toolbox\GFS Validation Experiments\All&T2.jpg, 51068 , 2008-07-22
GFS Toolbox\GFS Validation Experiments\All.fig, 40597 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\All.jpg, 44850 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\HighDensity.fig, 67475 , 2008-07-22
GFS Toolbox\GFS Validation Experiments\mix.fig, 22551 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\mix.jpg, 34819 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\mix.mat, 8768 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\pro.mat, 11825 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\TFS.mat, 17786 , 2008-07-22
GFS Toolbox\GFS Validation Experiments\TI.mat, 2980 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\tri.fig, 21375 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\tri.jpg, 33813 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\tri.mat, 7819 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\TT.mat, 3054 , 2008-07-22
GFS Toolbox\GFS Validation Experiments\TTS.mat, 695 , 2008-07-23
GFS Toolbox\GFS Validation Experiments\ValExpIT21-1.GFS, 1170 , 2009-02-11
GFS Toolbox\GFS Validation Experiments\ValExpIT21-2.GFS, 1278 , 2009-02-11
GFS Toolbox\GFS Validation Experiments\ValExpIT21-3.GFS, 1155 , 2009-02-11
GFS Toolbox\GFS Validation Experiments\ValExpST1-3.GFS, 936 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\ValExpST1-L.GFS, 928 , 2008-07-20
GFS Toolbox\GFS Validation Experiments\ValExpST1-R.GFS, 931 , 2008-07-20
GFS Toolbox\GFS Validation Experiments\ValExpST2-L.GFS, 982 , 2008-07-20
GFS Toolbox\GFS Validation Experiments\ValExpST2-R.GFS, 988 , 2008-07-20
GFS Toolbox\GFS Validation Experiments\ValExpST3-L.GFS, 923 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\ValExpST3-R.GFS, 923 , 2008-07-21
GFS Toolbox\GFS Validation Experiments\ValExpTT21-1.GFS, 1397 , 2009-02-11
GFS Toolbox\GFS Validation Experiments\ValExpTT21-2.GFS, 1411 , 2009-02-11
GFS Toolbox\GFS Validation Experiments\wide.mat, 8703 , 2008-07-21
GFS Toolbox\guictrl.m, 5308 , 2009-06-09
GFS Toolbox\IO.fig, 3167 , 2008-06-23
GFS Toolbox\IO.m, 5747 , 2008-06-23
GFS Toolbox\IRIS Data Problem, 0 , 2019-03-17
GFS Toolbox\IRIS Data Problem\Chromosom.m, 1807 , 2008-07-27
GFS Toolbox\IRIS Data Problem\Implementation of Evolutionary Fuzzy Systems.pdf, 227409 , 2008-07-22
GFS Toolbox\IRIS Data Problem\IRIS DATA.xls, 146944 , 2008-07-24
GFS Toolbox\IRIS Data Problem\IRIS GA, 0 , 2019-03-17
GFS Toolbox\IRIS Data Problem\IRIS GA\backgensys.m, 3399 , 2008-07-27
GFS Toolbox\IRIS Data Problem\IRIS GA\BG.mat, 2362 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\DESIRIS.fis, 993 , 2008-07-27
GFS Toolbox\IRIS Data Problem\IRIS GA\GA.mat, 15480 , 2008-07-31
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules, 0 , 2019-03-17
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\GA.mat, 12797 , 2008-07-31
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Gen3.fig, 8615 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Gen3.fis, 1468 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\gen30rulesys.m, 3113 , 2008-07-31
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Gen4.fig, 8435 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Gen4.fis, 1455 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Gen5.fig, 9405 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Gen5.fis, 1459 , 2008-07-29
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\init30rulepop.m, 2908 , 2008-07-31
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\IRIS.mat, 1339 , 2008-07-27
GFS Toolbox\IRIS Data Problem\IRIS GA\GA30Rules\Rayleigh.mat, 24038 , 2008-08-03

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  • jiansuo_shili
    说明：  刚刚接触图像检索的同学，对基于特征的图像检索还没有什么概念，利用这个小的程序（里面附有图像和实例）感受一下过程，对于继续研究很有帮助。(Contact with students just image retrieval, the feature-based image retrieval has no concept of, take advantage of this little program (inside with images and examples) feel the process and continue to study for the useful.)
    2010-03-18 15:00:41下载
    积分：1
  • ofdm_lbfgs
    Main fuction is to reduce PAPR of OFDM by LBFGS scheme
    2011-06-09 23:56:45下载
    积分：1
  • distribution-system
    distribution-system in the matlab mfile
    2013-09-20 12:00:39下载
    积分：1
  • bulangyundong2
    matlab 程实 实现布朗运动 源程序(matlab source Brownian motion process to achieve real)
    2011-08-02 11:27:16下载
    积分：1
  • cvx-zuiquan
    关于凸优化资料，目前最新版本的matlab图优化工具加载方法和学习算例。里面讲述了多目标优化、内点法等一些凸优化具体算例，希望对大家有用。(About convex optimization data, the latest version of the loading method matlab figure optimization tools and learning examples. Which describes a multi-objective optimization, interior point method and some convex optimization numerical example, we want to be useful.)
    2014-02-16 10:37:33下载
    积分：1
  • Robust-methods
    主要利用稳健方法比如迭代算法来对跳频信号在Alpha稳定分布噪声环境下进行参数估计(Main advantage of robust methods such as iterative algorithm for frequency-hopping signals Alpha stable distribution parameter estimation in noisy environments)
    2020-07-10 17:28:54下载
    积分：1
  • why
    file contains matlab program file contains matlab program file contains matlab program
    2011-09-15 15:27:43下载
    积分：1
  • studyTC_v1.1.chm
    详细的Total Commander帮助文档，可以帮助使用者迅速上手入门(Detailed Total Commander help document, can help users get up and running quickly entry)
    2012-08-29 09:53:38下载
    积分：1
  • code
    1.采用C均值聚类算法对男女生样本数据中的身高、体重2个特征进行聚类分析，考察不同的类别初始值以及类别数对聚类结果的影响，并以友好的方式图示化结果。 2.采用分级聚类算法对男女生样本数据进行聚类分析。分别尝试采用身高，体重，喜欢数学，喜欢文学，喜欢运动，喜欢模式识别共6个特征，以及身高，体重2个特征进行聚类，对比聚类结果，并以友好的方式图示化结果 (1. The use of C means clustering algorithm on sample data for boys and girls in the height, weight 2 characterized in cluster analysis to investigate the initial values of the different categories and the effect on the number of classes of the clustering result, and in a friendly way of illustration result. 2. Using hierarchical clustering algorithm to male and female students sample data clustering analysis. Try both using height, weight, like math, like literature, like sports, like pattern recognition feature a total of six, as well as height, weight, two features clustering, comparing clustering results, and in a friendly way of illustration of the results)
    2020-11-24 21:19:33下载
    积分：1
  • OFDM
    文件是OFDM的系统仿真程序！通过matlab仿真平台来实现！(The system file is OFDM simulation program! Matlab simulation platform adopted to achieve!)
    2009-05-20 23:58:51下载
    积分：1
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