title: Towards Identification of Wiener Systems with the Least Amount of a priori Information: IIR Cases.
abstract: In this paper, we investigate what constitutes the least amount of a priori information on the nonlinearity so that the linear part is identifiable in the non-Gaussian input case. Under the white noise input, three types of a priori information are considered including quadrant information, point information and monotonic information. In all three cases, identifiability has been established and the corresponding nonparametric identification algorithms are developed along with their convergence proofs.
authors.affiliation: Dept. of Electrical and Computer Engineering, University of Iowa, Iowa City, Iowa 52242.
authors.forename: Er-Wei
authors.initials: EW
authors.lastname: Bai
authors.forename: John
authors.initials: J
authors.lastname: Reyland
keywords: a priori information; nonlinear systems; system identification; wiener systems