GMM GMR代码

代码说明：

说明：  利用高斯回归进行数据预测，有实例和注释，可供参考学习(Using Gaussian regression to predict data, there are examples)

文件列表：

GMM, 0 , 2018-03-22
GMM\GMM-GMR-v2.0, 0 , 2018-03-22
GMM\GMM-GMR-v2.0\data, 0 , 2009-04-03
GMM\GMM-GMR-v2.0\data\data1.mat, 7384 , 2008-04-18
GMM\GMM-GMR-v2.0\data\data2_a.mat, 9784 , 2008-04-18
GMM\GMM-GMR-v2.0\data\data2_b.mat, 1800 , 2008-04-18
GMM\GMM-GMR-v2.0\data\data3_a.mat, 7392 , 2008-04-18
GMM\GMM-GMR-v2.0\data\data3_b.mat, 7392 , 2008-04-18
GMM\GMM-GMR-v2.0\demo1.m, 4986 , 2018-03-21
GMM\GMM-GMR-v2.0\demo2.m, 4469 , 2009-07-22
GMM\GMM-GMR-v2.0\demo3.m, 6157 , 2009-07-22
GMM\GMM-GMR-v2.0\EM.m, 5553 , 2009-07-22
GMM\GMM-GMR-v2.0\EM_init_kmeans.m, 1645 , 2009-07-22
GMM\GMM-GMR-v2.0\gaussPDF.m, 958 , 2009-07-22
GMM\GMM-GMR-v2.0\GMR.m, 5374 , 2018-03-22
GMM\GMM-GMR-v2.0\plotGMM.m, 1985 , 2009-07-22
GMM\task-parameterized-tensor-GMM-with-LQR, 0 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\data, 0 , 2014-02-11
GMM\task-parameterized-tensor-GMM-with-LQR\data\DataLQR01.mat, 43247 , 2014-02-02
GMM\task-parameterized-tensor-GMM-with-LQR\demo01.m, 8715 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\demo_testLQR01.m, 2328 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\demo_testLQR02.m, 2537 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\EM_tensorGMM.m, 3113 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\estimateAttractorPath.m, 2163 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\gaussPDF.m, 877 , 2014-02-02
GMM\task-parameterized-tensor-GMM-with-LQR\init_tensorGMM_timeBased.m, 1123 , 2014-02-02
GMM\task-parameterized-tensor-GMM-with-LQR\plotGMM.m, 938 , 2014-02-02
GMM\task-parameterized-tensor-GMM-with-LQR\readme.txt, 1907 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\reproduction_DS.m, 1384 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\reproduction_LQR_finiteHorizon.m, 3189 , 2014-06-18
GMM\task-parameterized-tensor-GMM-with-LQR\reproduction_LQR_infiniteHorizon.m, 2149 , 2014-06-18