Regions of constrained maximum likelihood parameter identifiability

This short paper considers the parameter identification problem of general discrete-time, nonlinear, multiple input-multiple output dynamic systems with Gaussian, white distributed measurement errors. Knowledge of the system parameterization is assumed to be known. Regions of constrained maximum likelihood (CML) parameter identifiability are established. A computation procedure employing interval arithmetic is proposed for finding explicit regions of parameter identifiability for the case of linear systems.