Parametric identification of linear noisy input-output systems

An efficient method is proposed for identification of linear noisy input-ou tput systems. Central to this method is that the variances of the input and output noises, which determine the bias in the ordinary least-squares (LS) estimator, are estimated in the way of increasing the degrees of both the denominator and the numerator of the system transfer function by one, but w ith no need to evaluate the average LS errors. While achieving estimation u nbiasedness, the proposed method exhibits algorithmic advantages over the L S-based algorithms recently developed. Performance comparisons with other e xisting estimation algorithms based upon computer simulations are given.