title: Identification of time-varying Hammerstein systems from ensemble data.
abstract: In this paper, we describe a new technique to identify rapidly time-varying Hammerstein systems from ensembles of input-output realizations. The technique involves two steps. A correlation approach is first used to obtain initial estimates of the linear subsystem parameters for every sampling time. An iterative optimization algorithm is then employed to produce final estimates of the system parameters. The input does not need to be white. The technique was tested on simulated data and was found to produce excellent results under realistic conditions.
authors.affiliation: Department of Biomedical Engineering, McGill University, Montréal, Québec, Canada.
authors.forename: M
authors.initials: M
authors.lastname: Lortie
authors.forename: R E
authors.initials: RE
authors.lastname: Kearney
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D001698:Biomedical Engineering; D016014:Linear Models; D008954:Models, Biological; D017711:Nonlinear Dynamics