Estimation of structured covariance matrices and multiple window spectrum analysis
An intimate relationship between low rank modeling and multiple window spectrum estimation is demonstrated by using maximum likelihood estimates of structured covariance matrices. The power in a narrow spectral band is estimated by estimating the variances in a low rank signal plus noise covariance model. This model is swept through the entire frequency band to obtain an estimate of power as a function of frequency. The resulting spectrum estimates are given by weighted combinations of eigenspectra. Each eigenspectrum results from projecting the data onto an orthogonal component of the signal ...
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