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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.13/30085

Title: Aspects of linear estimation in H∞
Author/Creator: Ninness, Brett
Description: A recent but rapidly maturing field in the area of system identification has been that of estimation in H∞. Greatly influencing this work has been the phenomenon that no linear in the data algorithm exists which is robustly convergent. This paper conducts a study of the nature of this issue by combining specific new analysis together with existing results from the mathematics literature on the topic of polynomial approximation theory. Particular attention is paid in this paper to the role of model order, and this leads to the consideration of model order selection from a deterministic worst case perspective.
Relation: International Journal of Control Vol. 72, Issue 15, p. 1402-1416
Publisher Link: http://dx.doi.org/10.1080/002071799220209
Date: 1999
Publisher: Taylor & Francis
Keyword(s): linear estimation; H∞; polynomial approximation theory
Resource Type: journal article
Rights: This is an electronic version of an article published in International Journal of Control Vol. 72, Issue 15, p. 1402-1416. International Journal of Control is available online at: http://www.tandfonline.com/openurl?genre=article&issn=0020-7179&volume=72&issue=15&spage=1402
Identifier: http://hdl.handle.net/1959.13/30085
Identifier: ISSN:0020-7179
Language: eng

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