Please use this identifier to cite or link to this item:
Title: Identification of Wiener systems with clipped observations
Authors: Li, Guoqi
Wen, Changyun
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2012
Source: Li, G., & Wen, C. (2012). Identification of Wiener systems with clipped observations. IEEE transactions on signal processing, 60(7), 3845-3852.
Series/Report no.: IEEE transactions on signal processing
Abstract: In this paper, we consider the parametric version of Wiener systems where both the linear and nonlinear parts are identified with clipped observations in the presence of internal and external noises. Also the static functions are allowed noninvertible. We propose a classification based support vector machine (SVM) and formulate the identification problem as a convex optimization. The solution to the optimization problem converges to the true parameters of the linear system if it is an finite-impulse-response (FIR) system, even though clipping reduces a great deal of information about the system characteristics. In identifying a Wiener system with a stable infinite-impulse-response (IIR) system, an FIR system is used to approximate it and the problem is converted to identifying the FIR system together with solving a set of nonlinear equations. This leads to biased estimates of parameters in the IIR system while the bias can be controlled by choosing the order of the approximated FIR system.
ISSN: 1053-587X
DOI: 10.1109/TSP.2012.2190404
Rights: © 2012 IEEE
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.