In the context of linear constrained optimization, we study in this paper the problem of finding an optimal solution satisfying all but of the given constraints. A solution is obtained by means of an algorithm of polynomial-time complexity. We then use these results to solve the problem of robust identification in the presence of outliers in the setting of bounded error parameter identification. Finally, we show that the estimate obtained converges to the true but unknown parameter in the presence of outliers.
Optimization with Few Violated Constraints for Linear Bounded Error Parameter Estimation
R Tempo;
2002
Abstract
In the context of linear constrained optimization, we study in this paper the problem of finding an optimal solution satisfying all but of the given constraints. A solution is obtained by means of an algorithm of polynomial-time complexity. We then use these results to solve the problem of robust identification in the presence of outliers in the setting of bounded error parameter identification. Finally, we show that the estimate obtained converges to the true but unknown parameter in the presence of outliers.File in questo prodotto:
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