登录
首页 » matlab » matlab-gpml

matlab-gpml

于 2021-03-16 发布
0 161
下载积分: 1 下载次数: 3

代码说明:

说明:  利用GPML-V4.1工具箱实现高斯过程回归(GPR)的多变量数据预测(Using gpml-v4.1 toolbox to realize multivariate data prediction of Gaussian process regression (GPR))

文件列表:

matlab-gpml\gp.m, 10560 , 2020-03-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\.octaverc, 8 , 2010-07-23
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\Copyright, 1837 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\apx.m, 39152 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\apxGrid.m, 38429 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\apxSparse.m, 2915 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\apxState.m, 20647 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covADD.m, 4141 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covConst.m, 533 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covCos.m, 1642 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covDiscrete.m, 2444 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covDot.m, 4125 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covEye.m, 1506 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covFBM.m, 2480 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covGabor.m, 2950 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covGaborard.m, 862 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covGaboriso.m, 747 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covGE.m, 1186 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covLIN.m, 878 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covLINard.m, 718 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covLINiso.m, 592 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covLINone.m, 1478 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covMaha.m, 8278 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covMask.m, 2077 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covMatern.m, 3060 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covMaternard.m, 992 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covMaterniso.m, 843 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covNNone.m, 2181 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covNoise.m, 808 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covOne.m, 1112 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covOU.m, 3690 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPER.m, 2825 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPERard.m, 707 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPeriodic.m, 1834 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPeriodicNoDC.m, 4121 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPERiso.m, 653 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPoly.m, 1728 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPP.m, 1920 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPPard.m, 940 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPPiso.m, 800 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covPref.m, 2069 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covProd.m, 3136 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covRQ.m, 1181 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covRQard.m, 1319 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covRQiso.m, 1165 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covScale.m, 3216 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSE.m, 1056 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSEard.m, 801 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSEiso.m, 704 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSEisoU.m, 685 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSEproj.m, 674 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSEvlen.m, 1229 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSM.m, 6966 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covSum.m, 2619 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covULL.m, 2120 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covW.m, 4131 , 2017-11-28
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covWarp.m, 1988 , 2017-11-28
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\cov\covZero.m, 1116 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\covFunctions.m, 7962 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\changelog, 257 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\checkmark.png, 198 , 2010-07-23
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoClassification.m, 4640 , 2017-11-27
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoGrid1d.m, 2968 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoGrid2d.m, 4208 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoMinimize.m, 910 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoRegression.m, 5188 , 2017-11-27
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoSparse.m, 3275 , 2016-10-18
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\demoState.m, 3125 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f0.gif, 26996 , 2016-10-19
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f1.gif, 4990 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f2.gif, 15082 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f3.gif, 13866 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f4.gif, 13141 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f5.gif, 19258 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f6.gif, 28470 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f7.gif, 31055 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f8.gif, 14698 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\f9.png, 159343 , 2016-10-28
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\gpml_randn.m, 1109 , 2010-07-23
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\index.html, 65841 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\manual.pdf, 529383 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\README, 21748 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\style.css, 77 , 2010-07-23
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usageClassification.m, 2660 , 2013-10-16
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usageCov.m, 3570 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usageLik.m, 2530 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usageMean.m, 2264 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usagePrior.m, 3472 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usageRegression.m, 2744 , 2016-10-11
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\doc\usageSampling.m, 2636 , 2013-01-17
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\gp.m, 10560 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infEP.m, 17986 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infGaussLik.m, 1838 , 2018-08-22
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infGrid.m, 10434 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infKL.m, 5936 , 2018-06-15
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infLaplace.m, 5464 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infLOO.m, 4085 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infMCMC.m, 11425 , 2016-08-25
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infPrior.m, 6113 , 2017-11-26
matlab-gpml\gpml-matlab-v4.2-2018-06-11\gpml-matlab-v4.2-2018-06-11\inf\infState.m, 4521 , 2018-06-15

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • wuguoqing1
    说明:  文章给出了水声波导模型下垂直阵和单水听器测鼍水下目标辐射噪声的误差和修正方法,以便使两种测量结果一致和 统一。(This paper gives a model acoustic waveguide vertical hydrophone array and a single measurement of underwater radiated noise Tuo error and correction method in order to make consistent and unified the two measurements.)
    2011-03-09 17:56:11下载
    积分:1
  • aufgabe1
    Beginning Example for matlab simulink
    2014-09-02 00:38:27下载
    积分:1
  • _FuzzyPID
    模糊控制器,能够实现模糊控制,自适应迷糊控制(Fuzzy Control)
    2011-10-24 15:36:37下载
    积分:1
  • NWA-Folder
    This folder contains Matlab functions for the Enhanced Interval Approach (EIA) in: Simon Coupland, J. M. Mendel and Dongrui Wu, “Enhanced Interval Approach for Encoding Words into Interval Type-2 Fuzzy Sets and Convergence of the Word FOUs,” IEEE World Congress on Computational Intelligence, Barcelona, Spain, July 2010. All following functions were tested in Matlab 7.4.0 (R2007a) under Windows 7: centroidIT2: Compute the centroid of an IT2 FS. EKM: Implement the Enhanced KM algorithms. IA: Implement the Interval Approach for word encoding. mainJPL: Illustrate IA and EIA using the JPL dataset. mainWeb: Illustrate IA and EIA using the Web dataset. mg: Compute the membership grades of a vector of numbers on a T1 FS. plotFigures: Plot Figs. 3.18, 3.19 and 3.20 in the book. plotIT2: Plot an IT2 FS. Last modified by Dongrui Wu (dongruiw@usc.edu), May 2, 2010.
    2013-12-19 03:02:01下载
    积分:1
  • wavelet-transform
    一维小波变换对信号进行去噪,小波包变换,对地震记录进行去噪(A one-dimensional wavelet transform for signal denoising, wavelet packet transform, the noise of seismic record)
    2016-04-12 14:26:12下载
    积分:1
  • DVHOP2
    基于粒子群的DV_hop算法的运用,有很好的效果,定位比较好(Algorithm based on particle swarm DV_hop use, have a good effect, better positioning)
    2011-10-23 20:34:06下载
    积分:1
  • MPSK
    QPSK仿真,误码率计算及其仿真结果的比较(QPSK )
    2010-02-26 14:04:24下载
    积分:1
  • GPC
    说明:  广义预测控制应用于预测控制,可以根据个人需要进行变换(GPC)
    2010-04-15 22:05:38下载
    积分:1
  • Delaunay
    delaunary三角剖分,在数据点较小的情况下,运行结果还算客观,但是数据点大于五万时,运行较慢。(Delaunary triangulation, data point in the case of small, the operation results is objective, but the data points is greater than fifty thousand, is running slower.)
    2014-12-09 21:44:53下载
    积分:1
  • Coding-for-COA_HighPrecision_high-convergence
    Coding for COA_High Precision_high convergence ***Cuckoo Optimization Algorithm*** * Matlab Toolbox Ver. 1.0.1 * programmed by: "Ramin Rajabioun, 2011" This code minimizes your cost function, so don t change any part of your code.
    2013-12-10 16:49:11下载
    积分:1
  • 696518资源总数
  • 105714会员总数
  • 27今日下载