The Markov random field is generally discrete. Of course there are continuous Markov random field, assuming that the Markov random field defined in a domain of U and above any X in U, Y (x) are subject to Gauss distribution, and between the two covariance function K (x, y) =G (x, y), where G is the corresponding Green function U, then this is a random field Markov random field, but also with the Gauss airport.

Filename	Size	Update
GMRF	0	2017-07-27
GMRF\GMRF	0	2018-01-18
GMRF\GMRF\Gmrf_12.m	190	2018-01-18
GMRF\GMRF\TestGMRF.m	312	2017-07-27
GMRF\GMRF\X_GmrfPara_2Order_Estimat.m	956	2015-10-26
GMRF\GMRF\X_GmrfPara_4Order_Estimat.m	948	2015-10-26
GMRF\GMRF\X_GmrfPara_5Order_Estimat.m	965	2017-07-27
GMRF\GMRF\X_Gmrf_ParaG.m	2114	2015-10-26
GMRF\GMRF\main_GMRF.m	1587	2017-10-18
GMRF\GMRF\texture.jpg	111945	2009-03-16
GMRF\MRFFeature.rar	104006	2015-10-26
GMRF\texture.jpg	111945	2009-03-16

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