Title :
The recursive linear identification method for ARMA model estimation
Author :
Liang, G. ; Wilkes, D.M.
Author_Institution :
Dept. of Electr. Eng., Vanderbilt Univ., Nashville, TN, USA
Abstract :
A novel recursive method for estimating the parameters of autoregressive moving-average (ARMA) models is presented. The recursive linear identification method is basically developed from an offline linear identification technique due to J. Durbin (1960). An integral part of this approach requires the fitting of a large order autoregressive model to the data. The appropriate choice of the size of this model is also discussed. Simulation results are given to illustrate the performance of the proposed algorithm
Keywords :
identification; parameter estimation; recursive functions; spectral analysis; statistical analysis; ARMA model estimation; autoregressive moving-average; parameter estimation; recursive linear identification method; spectral analysis; Computational modeling; Parameter estimation; Polynomials; Random processes; Recursive estimation; White noise;
Conference_Titel :
Southeastcon '92, Proceedings., IEEE
Conference_Location :
Birmingham, AL
Print_ISBN :
0-7803-0494-2
DOI :
10.1109/SECON.1992.202282
