FIR modeling using log-bispectra: Weighted least-squares algorithms and performance analysis

Maria Rangoussi, Georgios B. Giannakis

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations

Abstract

Identification of non-minimum-phase systems with finite impulse response (FIR) is addressed in the bispectrum domain. A phase retrieval algorithm, based on the log-bispectrum, is extended to log-magnitude reconstruction. Both linear-equation-based estimators are then combined to form an integrated, nonparametric system identification method. Weighted forms of these estimators are developed, which are asymptotically minimum-variance in the class of weighted least-squares estimators. Asymptotic variance expressions are derived for both the weighted and the unweighted forms. Theory and simulations illustrate that the approaches can identify non-minimum-phase MA (moving-average) models using output data which may be corrupted by additive Gaussian noise of unknown covariance.

Original languageEnglish (US)
Pages (from-to)2399-2402
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
StatePublished - Dec 1 1990
Event1990 International Conference on Acoustics, Speech, and Signal Processing: Speech Processing 2, VLSI, Audio and Electroacoustics Part 2 (of 5) - Albuquerque, New Mexico, USA
Duration: Apr 3 1990Apr 6 1990

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