please help me to solve bayesian compressive sensing code

clc; clear all; close all; %check if terminates? if count > 2 && abs(ML(count)-ML(count-1)) < (max(ML)-ML(count))*eta break; end % update alphas which = find(index==idx); if theta(idx) > 0 if ~isempty(which) % re-estimate Alpha = theta(idx); delta = Alpha-alpha(which); for k = 1:NT Sigii = Sig{k}(which,which); mui = mu{k}(which); Sigi = Sig{k}(:,which); ki = delta/(1+Sigii*delta); mu{k} = mu{k}-ki*mui*Sigi; Sig{k} = Sig{k}-ki*Sigi*Sigi'; comm = PHI{k}'*(phi{k}*Sigi); S(:,k) = S(:,k) + ki*(comm.^2); Q(:,k) = Q(:,k) + ki*mui*comm; G(:,k) = G(:,k) + ki*(Sigi'*PHIt(index,k))^2; end % alpha(which) = Alpha; else % adding Alpha = theta(idx); for k = 1:NT phii = PHI{k}(:,idx); Sigii = 1/(Alpha+S(idx,k)); mui = Sigii*Q(idx,k); comm1 = Sig{k}*(phi{k}'*phii); ei = phii-phi{k}*comm1; off = -Sigii*comm1; Sig{k} = [Sig{k}+Sigii*comm1*comm1', off; off', Sigii]; mu{k} = [mu{k}-mui*comm1; mui]; comm2 = PHI{k}'*ei; S(:,k) = S(:,k) - Sigii*(comm2.^2); Q(:,k) = Q(:,k) - mui*comm2; G(:,k) = G(:,k) - Sigii*(t{k}'*ei)^2; phi{k} = [phi{k},phii]; end % index = [index;idx]; alpha = [alpha;Alpha]; end else if ~isempty(which) % deleting for k = 1:NT Sigii = Sig{k}(which,which); mui = mu{k}(which); Sigi = Sig{k}(:,which); Sig{k} = Sig{k}-Sigi*Sigi'/Sigii; Sig{k}(:,which) = []; Sig{k}(which,:) = []; mu{k} = mu{k}-mui/Sigii*Sigi; mu{k}(which) = []; comm = PHI{k}'*(phi{k}*Sigi); S(:,k) = S(:,k) + (comm.^2)/Sigii; Q(:,k) = Q(:,k) + mui/Sigii*comm; G(:,k) = G(:,k) + (Sigi'*PHIt(index,k))^2/Sigii; phi{k}(:,which) = []; end % index(which) = []; alpha(which) = []; end end

%end % output weights = zeros(M,NT); for k = 1:NT weights(index,k) = mu{k}; end

[Walter Roberson]

You did not post an error message and you did not describe the difference between the output you get and the output you expect