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ooDACE-1.4

于 2017-06-24 发布 文件大小:4708KB
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代码说明：

  克里金matlab工具箱，可实现基于克里金的近似建模。(matlab Toolbox for Kriging)

文件列表：

ooDACE-1.4
ooDACE-1.4\ooDACE
ooDACE-1.4\ooDACE\@BasicGaussianProcess
ooDACE-1.4\ooDACE\@BasicGaussianProcess\BasicGaussianProcess.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\correlationFunction.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\cvpe.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\extrinsicCorrelationMatrix.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\fit.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\generateDegrees.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\getExpression.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\imse.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\intrinsicCovarianceMatrix.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\likelihood.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\marginalLikelihood.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\mseTestset.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\plotLikelihood.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\plotVariogram.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\predict.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\predict_derivatives.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\pseudoLikelihood.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\rcValues.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\regressionFunction.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\regressionMatrix.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\tuneParameters.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\updateModel.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\updateRegression.m
ooDACE-1.4\ooDACE\@BasicGaussianProcess\updateStochasticProcess.m
ooDACE-1.4\ooDACE\@BlindKriging
ooDACE-1.4\ooDACE\@BlindKriging\BlindKriging.m
ooDACE-1.4\ooDACE\@BlindKriging\Rmatrix.m
ooDACE-1.4\ooDACE\@BlindKriging\fit.m
ooDACE-1.4\ooDACE\@BlindKriging\polynomialCoding.m
ooDACE-1.4\ooDACE\@BlindKriging\posteriorBeta.m
ooDACE-1.4\ooDACE\@BlindKriging\regressionFunction.m
ooDACE-1.4\ooDACE\@BlindKriging\regressionMatrix.m
ooDACE-1.4\ooDACE\@CoKriging
ooDACE-1.4\ooDACE\@CoKriging\CoKriging.m
ooDACE-1.4\ooDACE\@CoKriging\correlationFunction.m
ooDACE-1.4\ooDACE\@CoKriging\extrinsicCorrelationMatrix.m
ooDACE-1.4\ooDACE\@CoKriging\fit.m
ooDACE-1.4\ooDACE\@CoKriging\intrinsicCovarianceMatrix.m
ooDACE-1.4\ooDACE\@CoKriging\regressionFunction.m
ooDACE-1.4\ooDACE\@CoKriging\regressionMatrix.m
ooDACE-1.4\ooDACE\@CoKriging\setData.m
ooDACE-1.4\ooDACE\@Kriging
ooDACE-1.4\ooDACE\@Kriging\Kriging.m
ooDACE-1.4\ooDACE\@Kriging\cvpe.m
ooDACE-1.4\ooDACE\@Kriging\getExpression.m
ooDACE-1.4\ooDACE\@Kriging\predict.m
ooDACE-1.4\ooDACE\@Kriging\predict_derivatives.m
ooDACE-1.4\ooDACE\@Kriging\setData.m
ooDACE-1.4\ooDACE\T2
ooDACE-1.4\ooDACE\T2\11D
ooDACE-1.4\ooDACE\T2\11D\Direct.m
ooDACE-1.4\ooDACE\T2\11D\ENRBF.m
ooDACE-1.4\ooDACE\T2\11D\ErrorMFRBF.m
ooDACE-1.4\ooDACE\T2\11D\F1.m
ooDACE-1.4\ooDACE\T2\11D\F2.m
ooDACE-1.4\ooDACE\T2\11D\F3.m
ooDACE-1.4\ooDACE\T2\11D\F4.m
ooDACE-1.4\ooDACE\T2\11D\HL1.fig
ooDACE-1.4\ooDACE\T2\11D\HL12.fig
ooDACE-1.4\ooDACE\T2\11D\HLF.m
ooDACE-1.4\ooDACE\T2\11D\MFRBF.m
ooDACE-1.4\ooDACE\T2\11D\MFRBFKriging.m
ooDACE-1.4\ooDACE\T2\11D\MFRSM.m
ooDACE-1.4\ooDACE\T2\11D\MY1.m
ooDACE-1.4\ooDACE\T2\11D\MY2.m
ooDACE-1.4\ooDACE\T2\11D\MYMLS.m
ooDACE-1.4\ooDACE\T2\11D\MYRBF.m
ooDACE-1.4\ooDACE\T2\11D\MYRSM.m
ooDACE-1.4\ooDACE\T2\11D\NEWTMRBF.m
ooDACE-1.4\ooDACE\T2\11D\P2HL2.fig
ooDACE-1.4\ooDACE\T2\11D\P2L1.fig
ooDACE-1.4\ooDACE\T2\11D\P2L1L2.fig
ooDACE-1.4\ooDACE\T2\11D\RBFcirle.m
ooDACE-1.4\ooDACE\T2\11D\RBFcirle1.m
ooDACE-1.4\ooDACE\T2\11D\RBFtest.m
ooDACE-1.4\ooDACE\T2\11D\RMSE1.m
ooDACE-1.4\ooDACE\T2\11D\RMSE2.m
ooDACE-1.4\ooDACE\T2\11D\RMSEMFRSM.m
ooDACE-1.4\ooDACE\T2\11D\RMSEMLS.m
ooDACE-1.4\ooDACE\T2\11D\RMSERBF.m
ooDACE-1.4\ooDACE\T2\11D\RMSERBFkriging.m
ooDACE-1.4\ooDACE\T2\11D\RMSEkriging.m
ooDACE-1.4\ooDACE\T2\11D\T2.m
ooDACE-1.4\ooDACE\T2\11D\TMFRBF2.m
ooDACE-1.4\ooDACE\T2\11D\TMFRBF3.m
ooDACE-1.4\ooDACE\T2\11D\TMFRBF31.m
ooDACE-1.4\ooDACE\T2\11D\TMFRBF32.m
ooDACE-1.4\ooDACE\T2\11D\TMFRBF41.m
ooDACE-1.4\ooDACE\T2\11D\TPLHS.m
ooDACE-1.4\ooDACE\T2\11D\Test.m
ooDACE-1.4\ooDACE\T2\11D\Test1.m
ooDACE-1.4\ooDACE\T2\11D\WI.m
ooDACE-1.4\ooDACE\T2\11D\YMFRBF.m
ooDACE-1.4\ooDACE\T2\11D\YMFRBF2.m
ooDACE-1.4\ooDACE\T2\11D\createTPLHD.m
ooDACE-1.4\ooDACE\T2\11D\createfigure.m
ooDACE-1.4\ooDACE\T2\11D\fitness.m

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0 个回复

  • qiuhe
    ％例15-1 NaN数据参与分析 a = magic(3) a(2,2) = NaN ％用NaN表示遗失数据 sum(a) ％对数据集进行求和( Example 15-1 NaN data involved in the analysis a = magic (3) a (2,2) = NaN missing data with NaN express sum (a) of data sets summation)
    2008-05-29 20:48:44下载
    积分：1
  • Szeliski.CV
    Computer Vision: Algorithms and Applications Richard Szeliski September 3, 2010 draft ⃝ c 2010 Springer
    2014-10-11 00:08:40下载
    积分：1
  • RANDOMINTERLEAVER
    simple IDMA TYPE RANDOM INTERLEAVER
    2014-01-22 00:47:09下载
    积分：1
  • TOPSIS
    说明：  Topsis Matlab function
    2019-11-28 16:24:23下载
    积分：1
  • 2modulesPppt
    A dynamic estimation of channel is necessary before the transmission of the signals since the wireless channel is time–varying..we use MMSE method for channel estimation. The MMSE method calculates the following, MMSE channel estimator is designed to minimize the estimation MSE. The MMSE estimate the channel responses.
    2013-11-13 18:24:50下载
    积分：1
  • example
    实现matlab很多功能的源代码，可能是书配的光盘(Achieve a lot of function in matlab source code, are probably book with CD-ROM)
    2009-03-27 08:11:57下载
    积分：1
  • harada
    It contains the source code for the OFDM simulation in different types of fading environment and under different schemes ike bpsk, gmsk, msk, etc.Also it contains the transmitter design for the OFDM
    2010-10-28 12:26:09下载
    积分：1
  • wireless
    erlang b The concept of trunking allows a large number of users to share relatively small number of channels in a cell. Two major classes of trunked radio systems : 1- blocked call cleared systems to describe this system erlang B formula is used. 2- blocked call delayed systems erlang c formula is used.
    2011-05-23 06:27:29下载
    积分：1
  • Digital-image-processing_advanced-course
    This is a pdf which tells about digital image processing
    2014-02-25 13:44:38下载
    积分：1
  • NumberRecognitionSystem
    本文论述并设计实现了一个脱机自由手写体数字识别系统。文中首先对待识别数字的预处理进行了介绍，包括二值化、平滑滤波、规范化、细化等图像处理方法；其次，探讨了如何提取数字字符的结构特征和笔划特征，并详细地描述了知识库的构造方法；最后采用了以知识库为基础的模板匹配识别方法,并以MATLAB作为编程工具实现了具有友好的图形用户界面的自由手写体数字识别系统。实验结果表明，本方法具有较高的识别率，并具有较好的抗噪性能。(In this paper, and design implementation of a freely Offline handwritten numeral recognition system. First, identify the figure of the pre-processing treatment were introduced, including binarization, smoothing filtering, standardization, refinement, such as image processing method Secondly, to explore how to extract the structural features of characters and stroke characteristics, and described in detail Knowledge of the construction method Finally the use of a Knowledge-based template matching to identify methods and MATLAB as a programming tool to achieve with a friendly graphical user interface of freely handwritten numeral recognition system. The experimental results show that this method has higher recognition rate, and has better anti-noise performance.)
    2009-03-13 21:32:51下载
    积分：1
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