Abstract
Abstract Using the modern time series analysis method, a new time-domain approach to multichannel optimal deconvolution is presented, by which asymptotically stable multichannel optimal deconvolution filters are presented in the autoregressive moving average (ARMA) innovation filter form and the corresponding Wiener deconvolution filters also are given. The signal and noise sources can be correlated. The new approach involves to construct the ARMA innovation model and to solve a Diophantine equation, and can handle the optimal deconvolution filtering, smoothing and prediction problems in a unified framework. A simulation example shows the usefulness of the new approach.
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