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On maximum likelihood identification of errors-in-variables models
- Bottegal, G. (author)
-
- Risuleo, Riccardo Sven (author)
- KTH,Reglerteknik,ACCESS Linnaeus Centre
- Zamani, M. (author)
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- Ninness, B. (author)
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- (creator_code:org_t)
- Elsevier, 2017
- 2017
- English.
- In: IFAC-PapersOnLine. - : Elsevier. - 2405-8963. ; 50:1, s. 2824-2829
- Journal article (peer-reviewed)
Abstract
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- In this paper, we revisit maximum likelihood methods for identification of errors-in-variables systems. We assume that the system admits a parametric description, and that the input is a stochastic ARMA process. The cost function associated with the maximum likelihood criterion is minimized by introducing a new iterative solution scheme based on the expectation-maximization method, which proves fast and easily implementable. Numerical simulations show the effectiveness of the proposed method.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)
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