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Modeling and Identification of LPTV Systems by Wavelets

We propose a novel model for discrete Linear Periodic Time Varying (LPTV) systems using wavelets. The new model is compared with the ''Raised model'', which is commonly used for modeling LPTV systems. The wavelets model will be shown to be particularly suitable for adaptive identification of LPTV systems. It offers a compromise between time- and frequency-based algorithms. Time resolution is needed for modeling reasons and minimizing processing delay. Frequency resolution enables faster convergence of adaptive algorithms in general and the Least Mean Square (LMS) algorithm used here, in particular. Simulations show that for a colored input using the new model results not only in faster convergence compared to the raised model based algorithm, but also produces a lower steady-state error. This, at no significant additional cost in numerical complexity.

Type of Seminar:
Public Seminar
Prof. Arie Feuer
Department of Electrical Engineering, Technion - Israel Institute of Technology, Haifa, Israel. Currently on sabbatical with: Signals, Systems and Control group, Dept. of Applied Physics, Delft University of Technology, Delft, The Netherlands.
Jul 04, 2001   17:15

ETH Zentrum, ETZ E6, Gloriastrasse 35, 8006 Zurich
Contact Person:

Prof. M. Morari
No downloadable files available.
Biographical Sketch:
B.Sc. and M.Sc. in Mechanical engineering at the Technion ('67 and '73 resp.). Ph.D. from Yale University on 1978. From 1967-1970 with Technomatics Inc. working on the design of automatic machines. 1978-1983 worked for Bell Labs in network performance evaluation. 1983 joined the faculty of Electrical Engineering at the Technion were he is currently a professor. Research interests include: 1. Super resolution in image processing. 2. Adaptive systems in signal processing and control. 3. Sampling and combined representations of signals and images.