Approximative weighting for a covariance-matching approach for identifying errors-in-variables systems

摘要

A covariance-matching approach for identifying errors-in-variables systems has previously been proposed and analyzed. It has been demonstrated that the gain in accuracy can be substantial if an optimal weighting is used. The computation of the optimal weighting requires knowledge of true parameters of signals and systems. This paper describes how the optimal weighting can be computed approximately from the available noisy data and thereby offers a way to identify errors-in-variables systems with high accuracy. Numerical examples indicate that using this approximately optimal weighting gives an accuracy that is close to the accuracy obtained by using the optimal weighting. Copyright © 2010 John Wiley & Sons, Ltd.