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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/12735

Title: Characterization of a class of non-Gaussian processes
Authors: Alshebeili, S.A.,
Venetsanopoulos, A.N.
Keywords: Computer Metatheory - Computational Complexity; Mathematical Techniques - Estimation; Signal Theory - Spectrum Analysis; Statistical Methods - Time Series Analysis
Issue Date: 1991
Publisher: Publ by IEEE, Piscataway, NJ, United States
Citation: Proceedings - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing Volume 5, 1991, Pages 3093-3096
Abstract: The problem of modeling of non-Gaussian processes generated by linear systems driven by white non-Gaussian process, and nonlinear systems driven by a white Gaussian process is addressed using the Volterra representation of systems. Cumulant-based approaches are developed for identifying the parameters of the proposed model when only a finite sample of received observations is available. It is shown that by using a partial set of the output cumulant samples, the computational complexity required in determining the kernels of the model is considerably reduced. The analysis is not restricted to special forms of the second-order Volterra system.
URI: http://hdl.handle.net/123456789/12735
ISSN: 07367791
Appears in Collections:College of Engineering

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