Reliability of Projection Algorithms in Conditional Estimation

A. Garulli, B. Z. Kacewicz, A. Vicino and G. Zappa
Additional contact information
A. Garulli: Università di Siena
B. Z. Kacewicz: Università di Siena
A. Vicino: Università di Siena
G. Zappa: Università di Firenze

Journal of Optimization Theory and Applications, 1999, vol. 101, issue 1, No 1, 14 pages

Abstract: Abstract This paper studies the role of projection algorithms in conditional set membership estimation. These algorithms are known to be suboptimal in terms of the worst-case estimation error. A tight upper bound on the error of central projection estimators and interpolatory projection estimators is computed as a function of the conditional radius of information. Since the radius of information represents the minimum achievable error, the derived bound provides a measure of the reliability level of the suboptimal algorithms. The results are derived in a general deterministic setting, which allows the consideration of linearly parametrized approximations of a compact set of feasible problem elements.

Keywords: Set membership estimation; linear models; projection algorithms; conditional estimation; worst-case error (search for similar items in EconPapers)
Date: 1999
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1023/A:1021710825323

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