On the Estimation of Time-varying Parameters in Transfer Function Models

1991 ◽  
pp. 301-324 ◽  
Author(s):  
Lennart Claesson ◽  
Anders H. Westlund
Keyword(s):  
Transfer Function ◽  
Time Varying ◽  
Varying Parameters ◽  
Time Varying Parameters ◽  
Function Models ◽  
Estimation Of Time ◽  
Transfer Function Models

Adaptive Estimation of Time-Varying Parameters in Linearly Parametrized Systems

2005 ◽  
Vol 128 (3) ◽  
pp. 691-695 ◽  
Author(s):  
Yongliang Zhu ◽  
Prabhakar R. Pagilla
Keyword(s):  
Adaptive Estimation ◽  
Parameter Estimate ◽  
Time Varying ◽  
Time Intervals ◽  
Varying Parameters ◽  
Time Varying Parameter ◽  
Time Varying Parameters ◽  
Parametrized Systems ◽  
Simulation Results ◽  
Estimation Of Time

Adaptive estimation of time-varying parameters in linearly parametrized systems is considered. The estimation time is divided into small intervals; in each interval the time-varying parameter is approximated by a time polynomial with unknown coefficients. A condition for resetting of the parameter estimate at the beginning of each interval is derived; the condition guarantees that the estimate of the time-varying parameter is continuous and also allows for the coefficients of the polynomial to be different in various time intervals. A modified version of the least-squares algorithm is provided to estimate the time-varying parameters. Stability of the proposed algorithm is shown and discussed. Simulation results on an example are given to validate the proposed method.

scholarly journals Transfer Function Models with Time-Varying Coefficients

2012 ◽  
Vol 2012 ◽  
pp. 1-31 ◽  
Author(s):  
Maria Sílvia de A. Moura ◽  
Pedro A. Morettin ◽  
Clélia M. C. Toloi ◽  
Chang Chiann
Keyword(s):  
Transfer Function ◽  
Least Squares Method ◽  
Estimation Procedure ◽  
Time Varying ◽  
Function Model ◽  
Varying Coefficients ◽  
Wavelet Expansions ◽  
Time Varying Coefficients ◽  
Function Models ◽  
Transfer Function Models

We consider a transfer function model with time-varying coefficients. We propose an estimation procedure, based on the least squares method and wavelet expansions of the time-varying coefficients. We discuss some statistical properties of the estimators and assess the validity of the methodology through a simulation study. We also present an application of the proposed procedure to a real pair of series.

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