calc_covar_prior

 CALC_COVAR_PRIOR image prior with distance-based interelement covar
 This is a simplification of exponential_covar_prior.m
 Reg= calc_covar_prior( inv_model )
 Reg        => output regularization 
 inv_model  => inverse model struct
 P_type--prior type
 1: elements are globally correlated
 2: elements within/without electrode rings are correlated to elements in same region.
 3: only elements within electrode rings are correlated.

0001 function Reg= calc_covar_prior( inv_model )
0002 % CALC_COVAR_PRIOR image prior with distance-based interelement covar
0003 % This is a simplification of exponential_covar_prior.m
0004 % Reg= calc_covar_prior( inv_model )
0005 % Reg        => output regularization
0006 % inv_model  => inverse model struct
0007 % P_type--prior type
0008 % 1: elements are globally correlated
0009 % 2: elements within/without electrode rings are correlated to elements in same region.
0010 % 3: only elements within electrode rings are correlated.
0011 
0012 % (C) 2007, Tao Dai and Andy Adler. Licenced under the GPL Version 2
0013 % $Id: calc_covar_prior.html 2819 2011-09-07 16:43:11Z aadler $
0014 
0015 % get average x,y,z of each element
0016 ff = inv_model.fwd_model;
0017 nel = size(ff.elems,1);
0018 eta = .1;%attenuation factor. eta is large when elems're spatially highly correlated
0019 
0020 dist = zeros(nel);
0021 
0022 z1 = ff.nodes(ff.electrode(1).nodes,3);%upper electrode ring
0023 z2 = ff.nodes(ff.electrode(end).nodes,3);%lower electrode ring
0024 
0025 for dim = 1: size(ff.nodes,2);
0026     coords = reshape(ff.nodes(ff.elems,dim),[size(ff.elems)]);%coord of four vertex of each elem
0027     m_coords = mean( coords,2);%calc center coord
0028     if dim == 3
0029         temp = double((m_coords<max(z1,z2))&(m_coords>min(z1,z2)));%regions of interests
0030         H = temp*temp';
0031         switch inv_model.fourD_prior.P_type %Prior type
0032             case 1 % all elements are correlated
0033                 H = eta*(ones(size(H)));
0034             case 2 % elements of ROI are not correlated with elements of non_ROI
0035                 temp = double(m_coords>max(z1,z2));
0036                 H = H + temp*temp';
0037                 temp = double(m_coords<min(z1,z2));
0038                 H = H + temp*temp';
0039                 H = eta*(H+1e-6);
0040             case 3 % elements are only correlated within ROI, non-ROI elements are highly attenuated
0041                 H = eta*(H+1e-6);
0042             otherwise
0043                 error('no such a 3-D prior type');
0044         end
0045     end
0046     difm = m_coords*ones(1,nel);
0047     difm = difm - difm';
0048     dist= dist + difm.^2;%
0049 end
0050 dist = sqrt(dist);%elements distance matrix
0051 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
0052 dist = dist/max(dist(:));
0053 
0054 Reg = exp(-dist ./ H);% 3-D elements correlations matrix.