Torokhti, A.Friedland, S.Howlett, P.G.2025-12-172025-12-1720072007 IEEE international symposium on information theory, 2007, pp.291-2959781424414291https://hdl.handle.net/1959.8/48111In this paper, we consider an extension and rigorous justification of Karhunen-Loève transform (KLT) which is an optimal technique for data compression. We propose and study the generic KLT which is treated as the best weighted linear estimator of a given rank under the condition that the associated covariance matrix is singular. As a result, the generic KLT is constructed in terms of the pseudo-inverse matrices that imply a development of the special technique. In particular, we give a solution of the new low-rank matrix approximation problem that provides a basis for the generic KLT. Theoretical aspects of the generic KLT are carefully studied. ©2007 IEEE.enCopyright IEEE 2007data compressionConference paper10.1109/ISIT.2007.4557241