Abstract
Easily computable recursive algorithms are proposed for estimating coefficients of A(z), C(z), and the covariance matrix Rw of wk for the multivariate ARMA process A(z)yk = C(z)wk on the basis of the noise-corrupted observations ηk Δ yk + εk. the estimates converge to the true ones under reasonable conditions. An illustrative example is provided, and the simulation results are shown to be consistent with the theoretical analysis.
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