Abstract
This paper considers the parametric identification of large-scale systems from noise-corrupted output observations. Computational tractability is achieved using perturbation techniques for decoupling and system-order reduction. The influence of the state variable model assumed for the original system on the performance of the identification system is discussed. Examples are given which demonstrate the effectiveness of the identification techniques.

This publication has 4 references indexed in Scilit: