Two linear stochastic processes may be separated using the Wiener filter. This takes on a particularly simple form if one process is from a known autoregressive (AR) model, and the other has unknown spectral characteristics (and one assumes its covariance matrix to be a scalar multiple of the identity matrix). This is because the inverse of the covariance matrix C is essentially the square of the...
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