Identification of a class of nonlinear systems under stationary non-Gaussian excitation

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Identification of a class of nonlinear systems under stationary non-Gaussian excitation

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Title: Identification of a class of nonlinear systems under stationary non-Gaussian excitation
Author: Ralston, J.C.; Zoubir, A.M.; Boashash, B
Abstract: This paper provides new solutions to the nonlinear system identification problem when the input to the system is a stationary non-Gaussian process. We propose the use of a model called the Hammerstein series, which leads to significant reductions in both the computational requirements and the mathematical tractability of the nonlinear system identification problem. We show that unlike the Volterra series, one can obtain closed-form expressions for the Hammerstein series kernels and the quadratic coherence function in the non-Gaussian case. Estimation of the kernels and quadratic coherence function is discussed. A comparison with a nonlinear system identification approach that uses the Volterra series is provided. An automotive engineering application illustrates the usefulness of the proposed method.
Description: This paper presents a method for non-linear system identification using a non-gaussian input. (The most recent upgrade of the original software package that calculates Time-Frequency Distributions and Instantaneous Frequency estimators can be downloaded from the web site: www.time-frequency.net. This was the first software developed in the field, and it was first released publicly in 1987 at the 1st ISSPA conference held in Brisbane, Australia., and then continuously updated).
URI: http://hdl.handle.net/10576/10720
Date: 1997-03

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