  A backward biorthogonalization approach is proposed, which modifies
biorthogonal functions so as to generate orthogonal projections onto a reduced
subspace. The technique is relevant to problems amenable to be represented by a
general linear model. In particular, problems of data compression, noise
reduction and sparse representations may be tackled by the proposed approach.
