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Risk adjusted identification of a class of nonlinear systems

Authors: Mario Sznaier; Constantino Lagoa; Wenjing Ma;

Risk adjusted identification of a class of nonlinear systems

Abstract

This paper addresses the problem of identification of a class of nonlinear systems from a set-membership standpoint. Specifically we consider structures consisting of the interconnection of a linear time invariant plant and a sector bound static nonlinearity. This structure includes as special cases, Hammerstein, Wiener and Hammerstein-Wiener systems. Our main result shows that, by pursuing a risk-adjusted approach, the problem can be reduced to a convex LMI optimization form that can be efficiently solved. In addition we provide a convergence analysis that points to an intrinsic limitation of any interpolatory algorithm. These results are illustrated with a simple example.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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