On Using a Genetic Algorithm in the Designing of Linear Digital Filters

Authors

  • Jacek Stelmach ETA Gliwice Sp. z o.o.

DOI:

https://doi.org/10.18778/0208-6018.346.07

Keywords:

digital filters, genetic algorithm, ARMA process

Abstract

Digital filters, either as filters with moving average (Finite Impulse Response) or autoregressive filters (Infinite Impulse Response), are widely used in noise suppression, signal processing or extracting information from data streams. Although well‑known theory allows for optimal parameter selection, there still exist such real applications where requirements limit the use of digital filters. One of the most important limitations is the response time delay caused by too many used lagged input signals. The method proposed in the article allows us to estimate filter parameters with a genetic algorithm, decreasing its delay but keeping the requirements important for the user (e.g.: attenuation). Transfer functions of such filters were compared with transfer functions of the most known classical filters.

Downloads

Download data is not yet available.

References

Cryer J. D., Chan K.‑S. (2008), Time Series Analysis with Applications in R, Springer Science, Berlin.
Google Scholar

Goldberg D. (1989), Genetic Algorithms in Search, Optimization and Machine Learning, Addison‑Wesley, Boston.
Google Scholar

Grzymkowski R., Kaczmarek K., Kiełtyka S., Nowak I. (2008), Wybrane algorytmy optymalizacji. Algorytmy genetyczne. Algorytmy mrówkowe, Wydawnictwo Pracowni Komputerowej Jacka Skalmierskiego, Gliwice.
Google Scholar

Holland J. (1975), Adaptation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor.
Google Scholar

Kirchgassner G., Wolters J. (2007), Introduction to Modern Time Series Analysis, Springer‑Verlag, Berlin.
Google Scholar

Lutkepohl H. (2005), New Introduction to Multiple Time Series Analysis, Springer‑Verlag, Berlin.
Google Scholar

Stelmach J. (2014), On the use of genetic algorithms in the selection of predictors of parametric regression models, [in:] 32nd International Conference “Mathematical Methods in Economics 2014” in Olomouc, Conference Proceedings, pp. 968–973.
Google Scholar

Downloads

Published

2020-02-03

How to Cite

Stelmach, J. (2020). On Using a Genetic Algorithm in the Designing of Linear Digital Filters. Acta Universitatis Lodziensis. Folia Oeconomica, 1(346), 113–124. https://doi.org/10.18778/0208-6018.346.07

Issue

Section

Articles