EFFICIENT COMPUTATION OF CRAMER-RAO BOUNDS FOR THE TRANSFER FUNCTIONS OF MIMO STATE-SPACE SYSTEMS

摘要

The present contribution deals with the accuracy of the transfer function of state-space parametric models estimated under the prediction error identification framework. More precisely, we intend to propagate the Cramer-Rao bound usually available on the covariance matrix of the state-space parameter estimates to that of the coefficients of the corresponding input-to-output transfer function. A natural way to solve this problem is to take advantage of the Jacobian matrix of the state-space to transfer function transformation while applying Gauss' formula for evaluating the covariance of the transfer function coefficients. Here, we focus on the computational aspects of the evaluation of this Jacobian matrix.