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Maximum likelihood estimation of the parameters of nonminimum phase and noncausal ARMA models

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1 Author(s)
Rasmussen, K.B. ; Electron. Inst., Tech. Univ. Denmark, Lyngby, Denmark

The well-known prediction-error-based maximum likelihood (PEML) method can only handle minimum phase ARMA models. This paper presents a new method known as the back-filtering-based maximum likelihood (BFML) method, which can handle nonminimum phase and noncausal ARMA models. The BFML method is identical to the PEML method in the case of a minimum phase ARMA model, and it turns out that the BFML method incorporates a noncausal ARMA filter with poles outside the unit circle for estimation of the parameters of a causal, nonminimum phase ARMA model

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Signal Processing, IEEE Transactions on  (Volume:42 ,  Issue: 1 )