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Proceedings Paper

Multiscale system identification and estimation
Author(s): Dzu K. Le
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Paper Abstract

A formula for 'multiscale' representation of linear systems and stochastic processes is derived. The formula facilitates the synthesis of multiresolution analysis with linear systems theories. For example, it simplifies the use of scale-selective error metrics for system identification. This multiscale system identification framework yields closed form optimal solutions for non- parametric problems. Its 'wavelet-z-transform' version is a fast algorithm for the parametric case. Application of this method to nonlinear systems is also possible. In general, multiscale system identification is more effective for transient dynamics than classical time domain methods. Illustrations of this multiscale system identification method and comparison against time-domain approaches are presented.

Paper Details

Date Published: 7 June 1995
PDF: 12 pages
Proc. SPIE 2563, Advanced Signal Processing Algorithms, (7 June 1995); doi: 10.1117/12.211423
Show Author Affiliations
Dzu K. Le, NASA Lewis Research Ctr. (United States)

Published in SPIE Proceedings Vol. 2563:
Advanced Signal Processing Algorithms
Franklin T. Luk, Editor(s)

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