Journal article
Identifiability and convergence analysis of the MINLIP estimator
Automatica, Vol.51, pp.104-110
2015
DOI: 10.1016/j.automatica.2014.10.091
Abstract
This paper studies the problem of identifying a monotone Wiener system from observed, noiseless input-output signals. Specifically, we study identifiability of such systems, as well as the convergence properties of the recently introduced MINimal LIPschitz (MINLIP) estimator. This estimator finds a system with minimal complexity by exploiting ordering of the output samples. This makes the approach conceptual quite different from traditional identification schemes based on least squares, prediction errors, maximum likelihood or numerical projections. Sufficient conditions from which the result follows are given in terms of 'Rotational Complete Inputs (RCI)', a generalization of the notion of Persistency of Excitation (PE) as used for the study of linear identification methods. Finally, it is derived that a Gaussian i.i.d. sequence satisfies this RCI property, while any binary sequence does not.
Details
- Title: Subtitle
- Identifiability and convergence analysis of the MINLIP estimator
- Creators
- Liang Dai - Uppsala UniversityKristiaan Pelckmans - Uppsala UniversityEr-Wei Bai
- Resource Type
- Journal article
- Publication Details
- Automatica, Vol.51, pp.104-110
- DOI
- 10.1016/j.automatica.2014.10.091
- ISSN
- 0005-1098
- eISSN
- 1873-2836
- Grant note
- DOI: 10.13039/100000001, name: National Science Foundation, award: CNS-1329657, 247035; DOI: 10.13039/501100004963, name: Seventh Framework Programme, award: CNS-1329657, 247035; DOI: 10.13039/501100000781, name: European Research Council, award: CNS-1329657, 247035
- Language
- English
- Date published
- 2015
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984197197902771
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