Cross spectrum ML estimate

This work reports how to include general concepts of the one-dimensional MLM procedure in a two-channel problem of cross-spectrum estimation. It is shown in the sequel that there is no any problem in extrapolating the well-known procedures for auto-spectrum estimation to the cross-spectrum, if the original procedure can be explained as a filter bank analysis procedure. The resulting cross-spectrum estimate looks formally to satisfy the excellent features which the normalized maximum likelihood procedure, reported previously by the authors, does in the auto-spectrum problem as concerns with resolution a low-side lobe behavior.Peer Reviewe