Adaptive recursive least squares method for parameter estimation of autoregressive models
[ X ]
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Inderscience Enterprises Ltd
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The recursive least squares (RLS) methods are extremely used to find the solutions of problems in many areas, such as communication, signal processing, optimisation and control. In this paper the RLS algorithm is modified for parameter estimation of regression models, such as the pseudo-linear ARMA (PS-ARMA) model and output error autoregressive (OEAR) model. The adaptive filtering technique with random input-output is used in the proposed recursive parameter estimation (RPE) algorithm to recursively predict the exact set of parameters for any regression model. The proposed method works by predicting an output signal that is adaptively improved to approximate the desired filter output. The experimental results are provided to prove the effectiveness of the proposed method.
Açıklama
Anahtar Kelimeler
adaptive filter, autoregressive model, parameter estimation, random signals
Kaynak
International Journal of Applied Nonlinear Science
WoS Q Değeri
Q4
Scopus Q Değeri
Cilt
4
Sayı
1
