MSE estimates for multitaper spectral estimation and off-grid compressive sensing

LD Abreu, JL Romero - IEEE Transactions on Information …, 2017 - ieeexplore.ieee.org
IEEE Transactions on Information Theory, 2017ieeexplore.ieee.org
We obtain estimates for the mean squared error (MSE) for the multitaper spectral estimator
and certain compressive acquisition methods for multi-band signals. We confirm a fact
discovered by Thomson [Spectrum estimation and harmonic analysis, Proc. IEEE, 1982]:
assuming bandwidth W and N time domain observations, the average of the square of the
first K=⌊ 2NW⌋ Slepian functions approaches, as K grows, an ideal bandpass kernel for the
interval [-W, W]. We provide an analytic proof of this fact and measure the corresponding rate …
We obtain estimates for the mean squared error (MSE) for the multitaper spectral estimator and certain compressive acquisition methods for multi-band signals. We confirm a fact discovered by Thomson [Spectrum estimation and harmonic analysis, Proc. IEEE, 1982]: assuming bandwidth W and N time domain observations, the average of the square of the first K = ⌊2NW⌋ Slepian functions approaches, as K grows, an ideal bandpass kernel for the interval [-W, W]. We provide an analytic proof of this fact and measure the corresponding rate of convergence in L 1 norm. This validates a heuristic approximation used to control the MSE of the multitaper estimator. The estimates have also consequences for the method of compressive acquisition of multi-band signals introduced by Davenport and Wakin, giving MSE approximation bounds for the dictionary formed by modulation of the critical number of prolates.
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