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Robust local basis function algorithms for identification of time-varying FIR systems in impulsive noise environments
Abstract
While local basis function (LBF) estimation algorithms, commonly used for identifying/tracking systems with time-varying parameters, demonstrate good performance under the assumption of normally distributed measurement noise, the estimation results may significantly deviate from satisfactory when the noise distribution is of impulsive nature, for example, heavy-tailed or corrupted by outliers. This paper introduces a computationally efficient method to make LBF estimator robust, enhancing its resistance to impulsive noise. The study illustrates that, for polynomial basis functions, this modified LBF estimator can be computed recursively. Furthermore, it demonstrates that the proposed algorithm can undergo online tuning through parallel estimation and leave-one-out crossvalidation.
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Authors (4)
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Wojciech Żuławiński
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Agnieszka Wyłomańska
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Details
- Category:
- Conference activity
- Type:
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language:
- English
- Publication year:
- 2024
- Bibliographic description:
- Niedźwiecki M., Gańcza A., Żuławiński W., Wyłomańska A.: Robust local basis function algorithms for identification of time-varying FIR systems in impulsive noise environments// / : , 2024,
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/cdc56724.2024.10886649
- Sources of funding:
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- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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