Dr. Giorgio Casinovi – Publications
L1-Norm Convergence Properties of Correlogram Spectral Estimates
G. Casinovi
IEEE Transactions on Signal Processing
vol. 55, no. 9, pp. 4354–4365, September 2007
Abstract
This paper establishes the following results concerning the estimation
of the power spectrum of a single, deterministic, infinitely long signal.
a) If sx is the signal’s power spectral density, correlogram spectral
estimates obtained from increasingly longer signal segments tend to
sx*w/2? in the L1-norm, where w is the Fourier transform of the
window used to generate the estimates. b) The L1-norm of
sx ? sx*w /2? can be made arbitrarily small by an appropriate
choice of window. It is further shown that the accuracy of the spectral
estimates generated by a given window is related to a newly introduced
function, termed the windowing error kernel and that this function
yields bounds on the asymptotic error of the estimates. As an example,
correlogram spectral estimates are used to analyze spectral regrowth
in an amplifier.
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Last revised on January 14, 2014.