Abstract
The aim of the paper is to present the properties of an A.R, model with time varying coefficients and its use in signal identification procedures. The actual coefficient values are approximated by linear combinations of basis time functions — in our case Haar functions.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Grenier Y., Time dependent ARMA modeling of non-stationary signals, IEEE Trans. ASSP vol.31 no 4 pp 899–911, Aug.1983
Charbonnier L. et al., Identification Methods for Non-stationary Signals, Signal Processing III — Theories and Applications, I.T. Young, et al. (eds.), Elsevier science Publishers B.V.(North Holland), EURASIP 1986
Sawicki J., Models of Signals and Algorithms of Signal Synthesis (report — in Polish), Technical University of Poznan, 1989
Sz-Nagy B., Introduction to Real Functions and Orthogonal Expansions, Akademiai Kiado, Budapest 1964
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1990 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Sawicki, J. (1990). Models of Monstationary Signals Using Maak Expansions. In: Ameling, W. (eds) ASST ’90 7. Aachener Symposium für Signaltheorie. Informatik-Fachberichte, vol 253. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76062-4_21
Download citation
DOI: https://doi.org/10.1007/978-3-642-76062-4_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53124-1
Online ISBN: 978-3-642-76062-4
eBook Packages: Springer Book Archive