function [L,M,R, err]  = GLRAM(A, L, low1, low2, ITE)%------------------------------------------------------------------% Input   A: data matrix%         L: initial L0%         low1: row dimension of reduced representation M{i}%         low2: column dimension of reduced representation M{i}%         ITE: number of iterations% Output: L: left transformation%         M: reduced representation%         R: right transformation%         err: reconstruction error measured by RMSRE  %-------------------------------------------------------------------%[row, col] = size(A{1}); % row and column dimensions of A{i}n          = size(A,2); % number of data points%-------------------------------------------------------------------                                                                                                        for ite = 1:ITEMU = 0;for i =1:n     TU = L'* A{i};	     MU = MU + TU'*TU;end;[U0,D0,V0] = svd(MU);R = V0(:,1:low2);%------------------------------------------------------------------- NU = 0;for i =1:n     TV = A{i}*R;     NU =  NU + TV*TV';end;[U1,D1,V1] = svd(NU);L = V1(:,1:low1);end;%-------------------------------------------------------------------for i =1:n     M{i} = L'* A{i}*R;end;%  Compute the RMSRE value (reconstruction error) err =  ERROR(L, M, R, A, n);%-------------------------------------------------------------------%                  THE END OF THE MAIN PROGRAM%-------------------------------------------------------------------      function error = ERROR(L, M, R, A, n)%  SUBROUTINE TO COMPUTE THE RMSRE VALUEerror = 0;for i =1:n    A_const{i} = L*M{i}*R';    TEMP       = A{i} - A_const{i};    error      = error + norm(TEMP,'fro')^2;end;error = sqrt(error/n);