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The signal/noise separation problem is addressed in two different ways. The first method intends to approximate the noise covariance matrix with prediction error filters. The second method introduces a noise modeling operator in the fitting goal. Although both methods separate the noise from the signal, the subtraction method can also mitigate the effects of the correlation between signal and noise by incorporating a regularization term into the fitting goal.

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