1. A method for training a linear prediction filter for prediction of information, comprising: providing reference data; collecting observed data containing the reference data; identifying a reduced order Krylov subspace between the observed data and the reference data; and maximizing mutual data between the observed data and the reference data in the subspace to define at least one autoregressive weight for use in the linear prediction filter.