IEEE Transactions on Signal Processing · 1991 · 14 citations · 23 references
EngineeringMathematicsSystems EngineeringAlgorithmsDynamical SystemsTime Series AnalysisParameter EstimationState EstimationSystem IdentificationAutoregressive ModelsAutoregressive Moving Average ModelsAutoregressive ProcessesIdentification Of Dynamical SystemsModel IdentificationNonlinear System IdentificationParameter IdentificationState-space Identification
The authors present the LD/sup 2/-ARMA identifier, a novel algorithm that solves the essentially nonlinear autoregressive moving-averaged (ARMA) identification problem with a linear procedure, in two steps: an order selection algorithm followed by an ARMA parameter estimator. The determination of the AR and MA coefficients involves the solution of two dual systems of linear equations. These systems decouple the estimation of the autoregressive component from the estimation of the moving average component. The selection of the number of poles and of the number of zeros is accomplished by a scheme that minimizes the mismatch of the data to each proposed model. Simulated experiments on the proposed order selection procedure are presented.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
23
Modeling by shortest data description
J. Rissanen · Automatica · 1978 · 6K citations
Digital Spectral Analysis with Applications.
B. Porat, S.L. Marple · Mathematics of Computation · 1988 · 2.7K citations
Fitting autoregressive models for prediction
Hirotugu Akaike · Annals of the Institute of Statistical Mathematics · 1969 · 2.5K citations
Computing, Mathematics, Forecasting +11
Maximum entropy spectral analysis
John P. Burg · Medical Entomology and Zoology · 1967 · 1.9K citations