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Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation
Abstract
The problem of identification of a nonstationary autoregressive process with unknown, and possibly time-varying, rate of parameter changes, is considered and solved using the parallel estimation approach. The proposed two-stage estimation scheme, which combines the local estimation approach with the basis function one, offers both quantitative and qualitative improvements compared with the currently used single-stage methods.
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- Category:
- Conference activity
- Type:
- materiały konferencyjne indeksowane w Web of Science
- Title of issue:
- 2018 IEEE International Conference on Acoustics, Speech and Signal Processing strony 4344 - 4348
- ISSN:
- 1520-6149
- Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Niedźwiecki M., Ciołek M..: Two-Stage Identification of Locally Stationary Autoregressive Processes and its Application to the Parametric Spectrum Estimation, W: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing, 2018, Institute of Electrical and Electronics Engineers Inc.,.
- DOI:
- Digital Object Identifier (open in new tab) 10.1109/icassp.2018.8461634
- Verified by:
- Gdańsk University of Technology
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