function [r,p,M,dh] = wtlsini(d,w,m)% WTLSINI - Initial approximation for the WTLS problem.%% [r,p,M,dh] = wtlsini(d,w,m)%% D = [d1 ... dN] - data matrix, sd := size(D,1)% W - sd x N weight matrix (EWTLS problem), %     sd x sd x N tensor (WTLS problem), or %     sd.N x sd.N weight matrix for vec(d) (FWTLS)% m   - complexity specification, m < sd% R/P - parameters of kernel/image representation of the model% M   - WTLS misfit achieved by the model % DH  - data approximation% For initial approximation, we use the EWGTLS2 solution with% WL and WR, such that WL*WR' is the best rank-1 approx.% of W in the EWTLS case, or the matrix formed from the diagonal % elements of W1,...,WN in the WTLS case, or the matrix % formed from the diagonal of W in the FWTLS case. See Note 11.[sd,N] = size(d);% Check the given weight matrix and choose methodswitch size(w,2) case N  % EWTLS  [u,s,v] = svd(w); case sd % WTLS  % extract the diagonals of the weight matrics  ew = zeros(sd,N);  for i = 1:N    ew(:,i) = diag(w(:,:,i));  end    [u,s,v] = svd(ew); case sd*N % General    ew = reshape(diag(w),sd,N);  [u,s,v] = svd(ew);   otherwise  error('Wrong dimension of W.')end% Best rank-1 approximation of W or WEs  = sqrt(s(1));wl = abs(u(:,1) * s);wr = abs(v(:,1) * s);% Compute the EWGTLS2 approximation with these weights[r,p]  = gtls2(d,wl,wr,m);[M,dh] = mwtlsr(d,w,r);