Fast Implementation of Two-Dimensional APES and CAPON Spectral Estimators
Multidimensional Systems and Signal Processing
Recursive and fast recursive capon spectral estimators
EURASIP Journal on Applied Signal Processing
Multi-dimensional Capon spectral estimation using discrete Zhang neural networks
Multidimensional Systems and Signal Processing
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The problem of complex spectral estimation is of great interest in many applications. This paper studies the general class of the forward-backward matched-filterbank (MAFI) spectral estimators including the widely used Capon as well as the more recently introduced amplitude and phase estimation of a sinusoid (APES) methods. In particular, we show by means of a higher order expansion technique that the one-dimensional (1-D) Capon estimator underestimates the true spectrum, whereas the 1-D APES method is unbiased; we also show that the bias of the forward-backward Capon is half that of the forward-only Capon (to within a second-order approximation). Furthermore. We show that these results can be extended to the two-dimensional (2-D) Capon and APES estimators. Numerical examples are also presented to demonstrate quantitatively the properties of and the relation between these MAFI estimators