Stabilization of stationary and time-varying autoregressive models
- Resource Type
- Conference
- Authors
- Juntunen, M.; Tervo, J.; Kaipio, J.P.
- Source
- Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181) Acoustics, speech, and signal processing Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on. 4:2173-2176 vol.4 1998
- Subject
- Signal Processing and Analysis
Components, Circuits, Devices and Systems
Brain modeling
Stability
Electroencephalography
Predictive models
Linear predictive coding
Narrowband
Parameter estimation
Least squares methods
Polynomials
Physics
- Language
- ISSN
- 1520-6149
A method for the stabilization of stationary and time-varying autoregressive models is presented. The method is based on the hyperstability constrained LS-problem with nonlinear constraints. The problems are solved iteratively with Gauss-Newton type algorithm that sequentially linearizes the constraints. The proposed method is applied to simulated data in the stationary case and to real EEG data in the time-varying case.