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Abstract
In this paper we propose a solution to the problem of tracking quasi-periodically varying systems based on the local basis function (LBF) approach. Within this framework, parameter trajectories are locally approximated using linear combinations of specific functions of time known as basis functions. We derive both bias and variance characteristics of LBF estimators. Additionally, we demonstrate that the computational burden associated with LBF estimation algorithms can be significantly reduced, without sacrificing high estimation accuracy, by employing the computationally fast, approximate version of the LBF scheme.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2024
- Bibliographic description:
- Gańcza A., Niedźwiecki M.: Identification of Quasi-Periodically Varying Systems Using the Local Basis Function Approach// / : , 2024,
- DOI:
- Digital Object Identifier (open in new tab) 10.23919/eusipco63174.2024.10715241
- Sources of funding:
-
- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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