Abstract
When the problem of restricted complexity identification is addressed in a set membership setting, the selection of the worst-case optimal model requires the solution of complex optimization problems. This paper studies different classes of suboptimal estimators and provides tight upper bounds on their identification error, in order to assess the reliability level of the identified models. Results are derived for fairly general classes of sets and norms, in the framework of Information Based Complexity theory.
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© 1999 Springer-Verlag London Limited
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Garulli, A., Kacewicz, B., Vicino, A., Zappa, G. (1999). Suboptimal conditional estimators for restricted complexity set membership identification. In: Garulli, A., Tesi, A. (eds) Robustness in identification and control. Lecture Notes in Control and Information Sciences, vol 245. Springer, London. https://doi.org/10.1007/BFb0109864
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DOI: https://doi.org/10.1007/BFb0109864
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