The second step, which couples all the predictors, can be done by setting the rows of ¢ to the most significant left singular vectors of the predictor (weight) matrix Í Ù ½ Ù Ñ ℄, and setting Ú ¢Ù .
the structure matrix ¢ is computed so that the projection of the predictor matrix Í onto the subspace spanned by ¢'s rows gives the best approximation (in the least squares sense) of Í for the given row-dimension of ¢.