Regions of constrained maximum likelihood parameter identifiabilityThis 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. It is shown that if the vector of true parameters is locally CML identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the CML estimation sequence will converge to the true parameters.
Document ID
19770029606
Acquisition Source
Legacy CDMS
Document Type
Conference Proceedings
Authors
Lee, C.-H. (Iowa State Univ. of Science and Technology Ames, IA, United States)
Herget, C. J. (Iowa State University of Science and Technology, Ames, Iowa, United States)