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gpml-matlab-v1.3-2006-09-08

于 2020-02-26 发布
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说明：  高斯过程(GP)模型中推理和预测的实现。它实现了在《Rasmussen & Williams:机器学习的高斯过程》(麻省理工学院出版社，2006)和《Nickisch & Rasmussen:二进制高斯过程分类的近似》(JMLR, 2008)中讨论的算法。该函数的优点在于灵活性、简单性和可扩展性。该函数具有一定的灵活性，首先通过定义均值函数和协方差函数来确定遗传算法的性质。其次，它允许指定不同的推理过程，如精确推理和期望传播(EP)。第三，它允许指定似然函数，如高斯函数或拉普拉斯函数(用于回归)和累积逻辑函数(用于分类)。简单性是通过一个简单的函数和紧凑的代码实现的。可扩展性是通过模块化设计来保证的，允许为已经相当广泛的推理方法、均值函数、协方差函数和似然函数库轻松添加扩展。(Gaussian Processes for Machine Learning , the MIT press, 2006 and Nickisch & Rasmussen: Approximations for Binary Gaussian Process Classification , JMLR, 2008. The strength of the function lies in its flexibility, simplicity and extensibility. The function is flexible as firstly it allows specification of the properties of the GP through definition of mean function and covariance functions. Secondly, it allows specification of different inference procedures, such as e.g. exact inference and Expectation Propagation (EP). Thirdly it allows specification of likelihood functions e.g. Gaussian or Laplace (for regression) and e.g. cumulative Logistic (for classification). Simplicity is achieved through a single function and compact code.)

文件列表：

gpml-matlab, 0 , 2006-09-08
gpml-matlab\README, 3741 , 2006-09-08
gpml-matlab\doc, 0 , 2006-03-29
gpml-matlab\doc\classification.html, 34439 , 2006-03-27
gpml-matlab\doc\alg31.gif, 43172 , 2005-11-07
gpml-matlab\doc\style.css, 77 , 2006-01-30
gpml-matlab\doc\alg32.gif, 34064 , 2005-11-07
gpml-matlab\doc\index.html, 3349 , 2006-03-29
gpml-matlab\doc\alg35.gif, 66673 , 2006-02-10
gpml-matlab\doc\alg36.gif, 32226 , 2006-02-10
gpml-matlab\doc\alg51.gif, 60084 , 2006-01-31
gpml-matlab\doc\alg52.gif, 41085 , 2006-02-10
gpml-matlab\doc\figepp.gif, 17875 , 2006-03-10
gpml-matlab\doc\figepp2.gif, 23299 , 2006-03-10
gpml-matlab\doc\figlapp.gif, 17854 , 2006-03-09
gpml-matlab\doc\figlapp2.gif, 25557 , 2006-03-09
gpml-matlab\doc\regression.html, 16598 , 2006-03-29
gpml-matlab\doc\figl1.gif, 21386 , 2005-10-26
gpml-matlab\doc\alg21.gif, 31996 , 2005-10-26
gpml-matlab\doc\sparse-approx.html, 7738 , 2006-03-29
gpml-matlab\doc\fig2d.gif, 36772 , 2006-03-14
gpml-matlab\doc\fig2de1.gif, 35364 , 2006-03-14
gpml-matlab\doc\figlf.gif, 16078 , 2006-03-27
gpml-matlab\doc\fig2de2.gif, 42683 , 2006-03-14
gpml-matlab\doc\fig2de3.gif, 38483 , 2006-03-14
gpml-matlab\doc\fig2dl1.gif, 34059 , 2006-03-14
gpml-matlab\doc\fig2dl2.gif, 40431 , 2006-03-14
gpml-matlab\doc\fig2dl3.gif, 38375 , 2006-03-14
gpml-matlab\doc\figl.gif, 6109 , 2006-03-27
gpml-matlab\doc\figlm.gif, 16712 , 2006-03-27
gpml-matlab\gpml, 0 , 2006-09-08
gpml-matlab\gpml\binaryEPGP.m, 7565 , 2006-09-08
gpml-matlab\gpml\binaryLaplaceGP.m, 7940 , 2006-05-10
gpml-matlab\gpml\Contents.m, 2206 , 2006-04-07
gpml-matlab\gpml\Copyright, 775 , 2006-02-09
gpml-matlab\gpml\gprSRPP.m, 2963 , 2006-03-30
gpml-matlab\gpml\minimize.m, 8995 , 2006-09-08
gpml-matlab\gpml\solve_chol.c, 1236 , 2006-02-09
gpml-matlab\gpml\solve_chol.m, 991 , 2006-02-08
gpml-matlab\gpml\sq_dist.c, 1931 , 2006-02-08
gpml-matlab\gpml\sq_dist.m, 2186 , 2006-03-09
gpml-matlab\gpml\covMatern5iso.m, 1221 , 2006-03-24
gpml-matlab\gpml\covRQiso.m, 1486 , 2006-09-08
gpml-matlab\gpml\covMatern3iso.m, 1206 , 2006-03-24
gpml-matlab\gpml\covSEiso.m, 1349 , 2006-04-07
gpml-matlab\gpml\Makefile, 131 , 2006-03-29
gpml-matlab\gpml\covFunctions.m, 4136 , 2006-05-15
gpml-matlab\gpml\gpr.m, 2811 , 2006-03-27
gpml-matlab\gpml\covSEard.m, 1569 , 2006-03-24
gpml-matlab\gpml\covProd.m, 2582 , 2006-04-06
gpml-matlab\gpml\covLINone.m, 984 , 2006-03-27
gpml-matlab\gpml\covSum.m, 2400 , 2006-03-20
gpml-matlab\gpml\covNoise.m, 1065 , 2006-03-24
gpml-matlab\gpml\covNNone.m, 1778 , 2006-03-24
gpml-matlab\gpml\covRQard.m, 1660 , 2006-09-08
gpml-matlab\gpml\covPeriodic.m, 1085 , 2006-04-07
gpml-matlab\gpml\covLINard.m, 1046 , 2006-03-24
gpml-matlab\gpml\covConst.m, 758 , 2006-03-24
gpml-matlab\gpml-demo, 0 , 2006-03-29
gpml-matlab\gpml-demo\Contents.m, 791 , 2006-03-27
gpml-matlab\gpml-demo\data_6darm.mat, 22768 , 2006-02-27
gpml-matlab\gpml-demo\data_boston.mat, 57040 , 2006-03-29
gpml-matlab\gpml-demo\demo_ep_2d.m, 7012 , 2006-03-29
gpml-matlab\gpml-demo\demo_ep_usps.m, 6130 , 2006-03-29
gpml-matlab\gpml-demo\demo_gparm.m, 8178 , 2006-03-29
gpml-matlab\gpml-demo\demo_gprsparse.m, 6511 , 2006-03-29
gpml-matlab\gpml-demo\demo_laplace_2d.m, 7257 , 2006-03-29
gpml-matlab\gpml-demo\demo_laplace_usps.m, 6134 , 2006-03-29
gpml-matlab\gpml-demo\demo_gpr.m, 9382 , 2006-03-29

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  • matlab
    这是关于matlab语言学习的经验，其中包括两个txt文档很方便下载，可以在手机上看，写的很好，值得看看。(This is about the matlab language learning experience, including two txt documents easy to download, you can phone point of view, well written, it is worth a look.)
    2010-12-27 10:37:12下载
    积分：1
  • chengxu
    采用db3小波对信号进行六层分解，可以用作容错故障检测的源程序，我做的小论文就用的这个程序，没有错误(Using six db3 wavelet decomposition of the signal can be used as fault tolerance fault detection of the source, I made a small paper on the use of this program, no errors)
    2013-10-11 19:43:13下载
    积分：1
  • jdvad
    用短时平均能量值对干净的语音信号进行检测，可以区分语音和非语音部分(With short time average energy value to test the clean speech signal, can distinguish between voice and non-voice part )
    2013-11-04 22:12:20下载
    积分：1
  • mexopencv-master
    open cv software implementation is done
    2014-10-29 13:33:17下载
    积分：1
  • noisecomp
    Code for denoising images. This code differs from standard wavelet denoising techniques in that it uses non-orthogonal wavelets, and unlike existing techniques, ensures that phase information is preserved in the image. Phase information is of crucial importance to human visual perception. Also, this code does have an effective way of determining threshold levels automatically. (Code for denoising images. This code differs from standard wavelet denoising techniques in that it uses non-orthogonal wavelets, and unlike existing techniques, ensures that phase information is preserved in the image. Phase information is of crucial importance to human visual perception. Also, this code does have an effective way of determining threshold levels automatically.)
    2007-11-07 19:22:52下载
    积分：1
  • examenfinal
    La señ al x(t) = 2 cos(11.200πt) + 2cos (10.000 πt) cos (1.000 πt) se suma a una señ al de ruido blanco (coloreado) gausiano de banda limitada con media igual a cero y con una densidad espectral de potencia de 1 µ w/Hz hasta una frecuencia de 15.000 Hz y cero a frecuencias mayores.
    2010-09-16 09:37:48下载
    积分：1
  • 111
    多重信号处理算法的DOA测角，信噪比，快拍数，信号源数对功率谱的影响(matlab platform, multi-signal processing algorithms DOA angle, signal to noise ratio, the snapshot number, the source of the power spectrum of several)
    2012-06-11 10:42:49下载
    积分：1
  • chaoliujisuan
    电力系统中matlab潮流计算所需要的节点注入功率母线数据等等30、69节点(Node injection power bus data for power flow calculation of MATLAB in power system and so on)
    2019-05-06 16:16:05下载
    积分：1
  • G.723.1-v2r1a.tar
    ITU-T G.723.1 Speech Coder: Matlab implementation This package implements the speech coder and decoder. Full documentation is in the PDF file included with the package. The test folder has test programs for the coder and decoder (for Windows).
    2008-03-11 23:19:30下载
    积分：1
  • FromConvexProgrammingtoOptimizationoverPolynomials
    陆吾生教授学术报告：多项式规划讲稿 比较容易理解(Professor Lu Wusheng Academic Report: polynomial planning easier to understand speech)
    2009-10-27 10:23:45下载
    积分：1
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