A stochastic approach to estimation in H∞

Title: A stochastic approach to estimation in H∞
Creator: Ninness, Brett
Relation: Automatica Vol. 34, Issue 1, p. 405-414
Publisher Link: http://dx.doi.org/10.1016/S0005-1098(97)00219-7
Publisher: Elsevier
Resource Type: journal article
Date: 1998
Description: This paper examines the problem of system identification from frequency response data. Recent approaches to this problem, known collectively as "Estimation in H∞", involve deterministic descriptions of noise corruptions to the data. In order to provide "worst-case" convergence with respect to these deterministic noise descriptions, non-linear in the data algorithms are required. In contrast, this paper examines "worst-case" estimation in H infinity when the disturbances are subject to mild stochastic assumptions and linear in the data algorithms are employed. Issues of convergence, error bounds, and model order selection are considered.
Subject: estimation theory; algorithms; system identification; robust estimation; error analysis
Identifier: http://hdl.handle.net/1959.13/31204
Identifier: uon:2743
Identifier: ISSN:0005-1098
Language: eng
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