Refined Instrumental Variable Identification of Continuous-time OE and BJ Models from Irregularly Sampled Data

This paper looks at the problem of system identification from non-uniformly sampled input-output data. It describes how refined instrumental variable estimators can be derived to directly identify the parameters of continuous-time output error and Box-Jenkins transfer function models from irregularly sampled data. Monte Carlo simulation analysis is used to illustrate the properties of the proposed estimation schemes.