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Abstract
The problem of identification of a linear nonsta-tionary stochastic process is considered and solved using theapproach based on functional series approximation of time-varying parameter trajectories. The proposed fast basis func-tion estimators are computationally attractive and yield resultsthat are better than those provided by the local least squaresalgorithms. It is shown that two important design parameters –the number of basis functions and the size of the local analysisinterval – can be selected on-line in an adaptive way.
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- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2019
- Bibliographic description:
- Niedźwiecki M., Ciołek M., Gańcza A.: Fast Basis Function Estimators for Identification of Nonstationary Stochastic Processes// / : , 2019,
- DOI:
- Digital Object Identifier (open in new tab) 10.23919/eusipco.2019.8902739
- Sources of funding:
- Verified by:
- Gdańsk University of Technology
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