Title :
Stabilization of stationary and time-varying autoregressive models
Author :
Juntunen, M. ; Tervo, J. ; Kaipio, J.P.
Author_Institution :
Dept. of Appl. Phys., Kuopio Univ., Finland
Abstract :
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
Keywords :
Newton method; autoregressive processes; electroencephalography; least squares approximations; medical signal processing; parameter estimation; stability; Gauss-Newton type algorithm; hyperstability constrained LS-problem; iterative solution; parameter estimation; real EEG data; simulated data; stabilization; stationary AR model; time-varying autoregressive model; Brain modeling; Electroencephalography; Least squares methods; Linear predictive coding; Narrowband; Parameter estimation; Physics; Polynomials; Predictive models; Stability;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.681577
