MINIMUM-VARIANCE PREDICTION FOR LINEAR TIME-VARYING SYSTEMS

In this paper we study the problem of minimum variance prediction for linear time-varying systems. We consider the standard time-varying aut oregression moving average (ARMA) model and develop a predictor which guarantees minimum variance prediction for a large class of linear tim e-varying systems. The predictor is developed based on a pseudocommuta tion technique for dealing with noncommutativity of linear time-varyin g operators in a transfer operator framework. We also show connections between this input-output predictor and the Kalman predictor via an e xample. (C) 1997 Elsevier Science Ltd.