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Identification of Non Stationary ARMA Models Based on Matrix Forgetting
Fecha
1999-09-10Registro en:
Revista Computación y Sistemas; Vol. 3 No. 1
1405-5546
Autor
Medel -Juárez, J. J.
Institución
Resumen
Abstract. To identify time-varying matrix parameter participating
in ARMAX-model description, a new recursive procedure is suggested in this thesis. This algorithm presents a combination of recursive version of Instrumental Variable procedure together with Matrix Forgetting Factor. The asymptotic value of the identification error "in average" is shown to have a bound which turns out to be dependent on the rate of parameter changing as well as on the variance of noise to be applied. By Monte-Carlo method it was shown that identification performance index has a minimum within the set of matrix forgetting with a norm less then 1. The optimum value as well as the corresponding optimal matrix forgetting are dependent on unknown parameters of a given ARMAX model and also on statistic characteristics of the applied noises.