On autocorrelation estimation in mixed-spectrum Gaussian processes

Benjamin Kedem and Eric Slud

Stochastic Processes and their Applications, 1994, vol. 49, issue 2, 227-244

Abstract: Consistency issues related to autocorrelation estimation for Gaussian processes with mixed spectra are clarified. The sample autocorrelation is known not to be consistent when the spectrum contains spectral atoms. This fact is verified by computing explicitly its mean-square limit in terms of the random measure assigned to the atoms of the process. The alternative estimator constructed from the zero-crossing rate is likewise not consistent in general. However, it is consistent for a spectrum supported at a single frequency, or a spectrum for which the 'signal' and 'noise' have the exact same first-order autocorrelation. This is proved, using recent results from multiple Wiener-Itô integral expansions for level-crossing counts, by direct computation of the spectrum of the zero-crossing indicator process when the underlying process has a mixed spectrum. In general, regardless of the spectral type, the asymptotic zero-crossing rate admits values between the lowest and highest positive frequencies with probability one. For band-limited processes, this fact provides an easy way to assess the precision of functions of the zero-crossing rate.

Keywords: spectral; atoms; spectral; measure; ergodic; Wiener-Ito; integrals; filter; zero-crossing; rate (search for similar items in EconPapers)
Date: 1994
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