Noisy input/output system identification using cumulants and the Steiglitz-McBride algorithm

John M M Anderson, Georgios B. Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

By transforming the input/output system identification problem into the high signal to noise ratio (SNR) cumulant domain the Steiglitz-McBride algorithm is extended, yielding an autocumulant and cross-cumulant based approach for autoregressive moving average (ARMA) modeling. The autocumulant approach requires that the ARMA parameters be estimated by first estimating the cumulants of the ARMA parameters. The cross-cumulant formulation permits the ARMA parameters to be estimated directly. Possible convergence points and convergence issues are investigated. Simulations are presented to illustrate the performance of these algorithms.

Original languageEnglish (US)
Title of host publicationConference Record - Asilomar Conference on Circuits, Systems & Computers
PublisherPubl by Maple Press, Inc
Pages608-612
Number of pages5
ISBN (Print)0818624701
StatePublished - 1991
Event25th Asilomar Conference on Signals, Systems & Computers Part 1 (of 2) - Pacific Grove, CA, USA
Duration: Nov 4 1991Nov 6 1991

Publication series

NameConference Record - Asilomar Conference on Circuits, Systems & Computers
Volume1
ISSN (Print)0736-5861

Other

Other25th Asilomar Conference on Signals, Systems & Computers Part 1 (of 2)
CityPacific Grove, CA, USA
Period11/4/9111/6/91

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