On the Performance of Combined Detection Estimation in Convex Uncertainty Spaces

A. V. Sebald; A. H. Haddad

doi:10.1109/TAC.1979.1102106

On the Performance of Combined Detection Estimation in Convex Uncertainty Spaces

A. V. Sebald, A. H. Haddad

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Abstract

The performance of combined detector estimators (CDE’s) in the adaptive estimation problem is discussed. They provide better performance than robust single estimator designs. Suboptimal realizations are also shown to be useful in the linear quadratic (LQ) discrete-time case. Finally, a posteriori characterizations of suboptimal CDE risk are shown to be useful in determining whether to improve the near optimality by adding more estimators.

Original language	English (US)
Pages (from-to)	651-652
Number of pages	2
Journal	IEEE Transactions on Automatic Control
Volume	24
Issue number	4
DOIs	https://doi.org/10.1109/TAC.1979.1102106
State	Published - Aug 1979

ASJC Scopus subject areas

Control and Systems Engineering
Computer Science Applications
Electrical and Electronic Engineering

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10.1109/TAC.1979.1102106

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abstract = "The performance of combined detector estimators (CDE{\textquoteright}s) in the adaptive estimation problem is discussed. They provide better performance than robust single estimator designs. Suboptimal realizations are also shown to be useful in the linear quadratic (LQ) discrete-time case. Finally, a posteriori characterizations of suboptimal CDE risk are shown to be useful in determining whether to improve the near optimality by adding more estimators.",

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AB - The performance of combined detector estimators (CDE’s) in the adaptive estimation problem is discussed. They provide better performance than robust single estimator designs. Suboptimal realizations are also shown to be useful in the linear quadratic (LQ) discrete-time case. Finally, a posteriori characterizations of suboptimal CDE risk are shown to be useful in determining whether to improve the near optimality by adding more estimators.

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On the Performance of Combined Detection Estimation in Convex Uncertainty Spaces

Abstract

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