FIR Modeling Using Log-Bispectra: Weighted Least-Squares Algorithms and Performance Analysis

Maria Rangoussi, Georgios B. Giannakis

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

Identification of nonminimum phase systems with finite impulse response is addressed in the bispectrum domain. A bispectrum-based phase retrieval algorithm is modified to handle the phase wrapping problem, and 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 the above 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 new approaches can identify nonminimum phase MA models, using output-data that may be corrupted by additive Gaussian noise of unknown covariance. Due to their nonparametric nature, the proposed algorithms outperform existing linear equation cumulant-based modeling methods, in the case of model order mismatch.

Original languageEnglish (US)
Pages (from-to)281-296
Number of pages16
JournalIEEE transactions on circuits and systems
Volume38
Issue number3
DOIs
StatePublished - Mar 1991

Bibliographical note

Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.

Fingerprint Dive into the research topics of 'FIR Modeling Using Log-Bispectra: Weighted Least-Squares Algorithms and Performance Analysis'. Together they form a unique fingerprint.

Cite this