Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1205
Title: Robust filtering by fictitious noises
Authors: Zhang, Huanshui
Zhang, David D.
Wang, Wei
Xie, Lihua
Subjects: Robust
Filtering
Stochastic
Uncertainty
Innovation
Fictitious noise
Issue Date: 2003
Publisher: IEEE
Source: 42nd IEEE Conference on Decision and Control : December 9-12, 2003, Maui, Hawaii, USA : proceedings, v. 2, p. 1280-1284.
Abstract: In this paper, a new approach is presented for robust filtering of a linear discrete-time signal by applying fictitious noise. Modeling errors, in both the numerator and denominator of the transfer functions, are parameterized by using random variables with zero mean and known covariance. The robust performance is obtained by minimizing the mean square estimation error over all of the random parameter and noise. To derive a robust estimator, the uncertainties in the model are incorporated into two mutually uncorrelated fictitious noises with zero means. The covariances of the fictitious noises are computed by using two formulas that are presented in this paper. An illustrative example shows the effectiveness of our approach.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/1205
ISBN: 0-7803-7924-1
Appears in Collections:COMP Conference Papers & Presentations

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