Journal article
Stochastic and worst case system identification are not necessarily incompatible
Automatica (Oxford), Vol.30(9), pp.1491-1493
09/1994
DOI: 10.1016/0005-1098(94)90017-5
Abstract
Stochastic and worst case approaches to system identification are different and are usually treated separately. In this communique we investigate the effect that a projection operator has on the worst case behavior of estimates derived by stochastic identification algorithms. We show that under certain assumptions the projections of the stochastic estimates are convergent in the worst case setting. We illustrate this result by applying it to least squares and maximum likelihood algorithms.
Details
- Title: Subtitle
- Stochastic and worst case system identification are not necessarily incompatible
- Creators
- Er-Wei Bai - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242-1595, U.S.AMark S Andersland - Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, IA 52242-1595, U.S.A
- Resource Type
- Journal article
- Publication Details
- Automatica (Oxford), Vol.30(9), pp.1491-1493
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/0005-1098(94)90017-5
- ISSN
- 0005-1098
- eISSN
- 1873-2836
- Language
- English
- Date published
- 09/1994
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984083835202771
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