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Abstract
Accurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately chosen basis functions. The paper shows that tracking performance of the resulting local basis function estimation algorithms can be further improved by means of regularization. The method is illustrated by an important recent application - identification of fast time-varying acoustic channels used in underwater communication.
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- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.ifacol.2021.08.384
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
IFAC-PapersOnLine
no. 54,
pages 351 - 356,
ISSN: 2405-8963 - Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Niedźwiecki M., Gańcza A., Kaczmarek P.: Identification of Fast Time-varying Communication Channels Using the Preestimation Technique// IFAC-PapersOnLine -Vol. 54,iss. 7 (2021), s.351-356
- DOI:
- Digital Object Identifier (open in new tab) 10.1016/j.ifacol.2021.08.384
- Sources of funding:
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- Project Generalized Savitzky-Golay filters for identification and smoothing of nonstationary processes
- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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