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Abstract
In this paper we consider the problem of noncausal identification of nonstationary,linear stochastic systems, i.e., identification based on prerecorded input/output data. We show how several competing weighted least squares parameter smoothers, differing in memory settings, can be combined together to yield a better and more reliable smoothing algorithm. The resulting parallel estimation scheme automatically adjusts its smoothing bandwidth to the unknown, and possibly time-varying, rate of nonstationarity of the identified system. It also allows one to account for the distribution of measurement noise, and in particular - to cope with heavy-tailed disturbances, such as Laplacian noise, or light-tailed disturbances, such as uniform noise.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Title of issue:
- 18th IFAC World Congress, August 28 - September 2, 2011 Milano. - [CD] strony 7803 - 7808
- Language:
- English
- Publication year:
- 2011
- Bibliographic description:
- Niedźwiecki M., Gackowski S.: On noncausal identification of nonstationary stochastic systems// 18th IFAC World Congress, August 28 - September 2, 2011 Milano. - [CD]/ ed. eds. S. Bittanti, A. Cenedese, S. Zampieri Włochy: IFAC-International Federation of Automatic Control, 2011, s.7803-7808
- DOI:
- Digital Object Identifier (open in new tab) 10.3182/20110828-6-it-1002.00386
- Verified by:
- Gdańsk University of Technology
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