SGP

所属分类:人工智能/神经网络/深度学习
开发工具:matlab
文件大小:2009KB
下载次数:134
上传日期:2013-05-29 11:51:41
上 传 者w514400413
说明:  单输出高斯过程回归 代理模型 回归 可代替神经网络
(Single output Gaussian process regression)

文件列表:
SGP\1.jpg (20198, 2012-07-16)
SGP\2.jpg (20414, 2012-07-16)
SGP\3.jpg (20881, 2012-07-16)
SGP\AdjustAirfoil.m (1148, 2012-07-16)
SGP\AssembleOrDisassemble.asv (2401, 2012-07-16)
SGP\AssemblePara.asv (2160, 2012-07-16)
SGP\AssemblePara.m (2106, 2012-07-16)
SGP\CheckAirfoilFile.m (3256, 2012-07-16)
SGP\CirclePoint.asv (153, 2012-07-16)
SGP\CirclePoint.m (253, 2012-07-16)
SGP\command.txt (188, 2013-03-12)
SGP\Cov_matrix.asv (687, 2012-07-16)
SGP\Cov_matrix.m (682, 2012-07-16)
SGP\Cov_matrix_Deri.m (701, 2012-07-16)
SGP\Cov_Y.asv (1874, 2012-07-16)
SGP\Cov_Y.m (1867, 2012-07-16)
SGP\Cov_Y_Deri.asv (8590, 2012-07-16)
SGP\Cov_Y_Deri.m (8622, 2012-07-16)
SGP\delta.m (129, 2012-07-16)
SGP\DGPR_predict.asv (628, 2012-07-16)
SGP\DGPR_predict.m (624, 2012-07-16)
SGP\DisassemblePara.asv (1257, 2012-07-16)
SGP\DisassemblePara.m (1339, 2012-07-16)
SGP\example_circle.asv (999, 2012-07-16)
SGP\example_circle.m (1159, 2012-07-16)
SGP\example_circle_2.asv (2054, 2012-07-16)
SGP\example_circle_2.m (2074, 2012-07-16)
SGP\hs_err_pid3868.log (15143, 2012-07-16)
SGP\KMeanCluster.m (1721, 2012-07-16)
SGP\log_likelihood.asv (3412, 2012-07-16)
SGP\log_likelihood.m (3504, 2012-07-16)
SGP\main.asv (1312, 2012-07-16)
SGP\main_NACA.asv (4945, 2012-07-16)
SGP\main_NACA.m (2587, 2012-07-16)
SGP\MultipleGP.asv (2145, 2012-07-16)
SGP\MultipleGP.m (2255, 2012-07-16)
SGP\noise_sigma.mat (190, 2012-07-16)
SGP\optimize\matlab-win32\compileMex (1925, 2012-07-16)
SGP\optimize\matlab-win32\Contents.m (2505, 2012-07-16)
SGP\optimize\matlab-win32\CVS\Entries (889, 2012-07-16)
... ...

Using the SNOPT mex Files in $SNOPT/matlab ========================================== Run Matlab in the directory $SNOPT/matlab. Typing >> more on >> help Contents from Matlab provides an overview of the package. At the Matlab prompt, type >> runAllExamples This script sets the matlab path appropriately. The subdirectory ./examples contains various sample problems that demonstrate how to use the snOpt Matlab interfaces. Read the in-line help information for each m-file for more information. To run the individual m-files type >> setpath % if you haven't already called runAllExamples >> addpath examples >> addpath examples/snmain >> snmain

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