Strongly consistent output only and input/output identification in the presence of Gaussian noise

A. Delopoulos, G. B. Giannakis

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

10 Scopus citations

Abstract

Output only and input/output (I/O) system identification algorithms are developed based on a novel mean-square-error (MSE) criterion. The input is assumed non-Gaussian and the performance criterion implicitly exploits cumulant statistics to suppress the effect of additive Gaussian noise. The noise covariance need not be known, and in I/O problems both input and output (perhaps correlated) noises are allowed. Although expressed in terms of noisy data, the novel objective function is a scalar multiple of the standard MSE as if the latter was computed in the absence of noise. It yields strongly consistent parameter estimators which are obtained by solving linear equations via computationally attractive and noise insensitive recursive-least-squares and least-mean-squares algorithms. Simulations illustrate the performance of the proposed algorithms and they are compared them with the conventional methods.

Original languageEnglish (US)
Title of host publicationProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
PublisherPubl by IEEE
Pages3521-3524
Number of pages4
ISBN (Print)078030033
StatePublished - Dec 1 1991
EventProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91 - Toronto, Ont, Can
Duration: May 14 1991May 17 1991

Publication series

NameProceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing
Volume5
ISSN (Print)0736-7791

Other

OtherProceedings of the 1991 International Conference on Acoustics, Speech, and Signal Processing - ICASSP 91
CityToronto, Ont, Can
Period5/14/915/17/91

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