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Robust robust model reduction

Proceedings of the 2004 American Control Conference, 2004
The problem of linear model reduction is addressed. Given a state-space model of a linear time-invariant system, a model of prescribed order is obtained such that the H/sub 2/-norm of the difference between the transference of the two models is minimized. The reduced model is modeled as having the same order as the system but with a nonminimal observer
Y. Halevi, U. Shaked
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Robust Statistics [PDF]

open access: possible, 2011
The first example involves the real data given in Table 1 which are the results of an interlaboratory test. The boxplots are shown in Fig. 1 where the dotted line denotes the mean of the observations and the solid line the median. We note that only the results of the Laboratories 1 and 3 lie below the mean whereas all the remaining laboratories return ...
Gather, Ursula, Davies, P. Laurie
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Robustness and the robust estimate

Journal of Geodesy, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Robust Preferences and Robust Portfolio Choice

2009
This chapter focuses on the problems of robust preferences and robust portfolio choice. The problem of portfolio choice consists in choosing, among all the available positions, a position that is affordable, given the investor's wealth w , and which is optimal with respect to the investor's preferences.
Föllmer, Hans   +2 more
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Biological robustness

Nature Reviews Genetics, 2004
Robustness is a ubiquitously observed property of biological systems. It is considered to be a fundamental feature of complex evolvable systems. It is attained by several underlying principles that are universal to both biological organisms and sophisticated engineering systems.
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Model robustness in robust identification

Proceedings of 1995 34th IEEE Conference on Decision and Control, 2002
Considers the issue of model robustness. In particular the author considers fitting a linear transfer function model in the presence of a small deviation from linearity. The issue of deviation from linearity is often mentioned in robust identification but does not seem to have been explicitly treated before.
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