Improved ML cross-spectral estimation
Document typeConference report
Rights accessOpen Access
This work deals with the use of dedicated filters for cross-spectrum estimation. Basically, the ML cross-spectral estimator can be obtained as the natural extension of the Normalized Maximurn Likelihood procedure, reported previously by the authors, te the measurement of cross-power density for two data registers x(n) and y(nl. As an important improvement in present cross-spectrum estimation, the importance of the selection of the cross-correlation matrix estimator used as a starting point is included.
CitationLagunas, M., Gasull, A. Improved ML cross-spectral estimation. A: European Signal Processing Conference. "EUSIPCO 1986: Signal processing III: theories and applications proceedings of EUSIPCO-86: Third European Signal Processing Conference: The Hague, The Netherlands: September 2-5, 1986". Barcelona: 0, p. 255-258.