Balanced parametrization in time-series identification

The authors examine the identification of time-series, following a predictor-error approach using a novel parametrization for predictors. This parametrization relies on a canonical form for minimum-phase systems which utilizes a generalized notion of a balanced realization. In this framework an identification scheme involving only unconstrained optimizations is developed, and an approach to the order selection problem is suggested.<>