Statistical efficiency of the sample autocorrelation function in ARMA parameter estimation

S. P. Bruzzone, M. Kaveh

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Many modern ARMA spectral estimators are based either on the raw data or on some version of the lagged-product sample autocorrelation function (ACF). These two classes are compared in terms of their Cramer-Rao bound generalized variances in estimating the poles and zeros of the ARMA system generating the process. It is seen that the choice of lags of the sample ACF required to preserve most of the information in the data is signal dependent. Recommendations of a "good" information-preserving choice of lags for an AR(2) process in white noise are tabulated against pole magnitude and SNR. The case of two additive narrowband AR(2) processes is also studied.

Original languageEnglish (US)
Article number1171619
Pages (from-to)240-243
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 1982
Event1982 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 1982 - Paris, France
Duration: May 3 1982May 5 1982

Bibliographical note

Funding Information:
Supported in part by a University of Minnesota Dissertation Fellowship, Air Force Office of Scientific Research Grant #AFOSR—7S—362S, and

Funding Information:
Matomal Science Foundation Grant #ECS—81O5962.

Publisher Copyright:
© 1982 IEEE.


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