Identification of continuous-time models

The problem of estimating the transfer function of a continuous-time dynamic system in the presence of colored noise is considered. An operator transformation that allows for keeping a continuous-time parametrization is introduced; the parameter estimation can be made by means of a discrete-time maximum-likelihood algorithm. A comparison is made between the performance of the new method in comparison with a standard identification of an ARMAX (autoregressive moving-average with exogeneous input) model. The method is useful in cases where it is important to estimate the coefficients of a continuous-time transfer function and to maintain a physical interpretation of the transfer function results