Development of a method for synthesis the FIR filters with a cascade structure based on genetic algorithm

Authors

DOI:

https://doi.org/10.15587/2706-5448.2021.237271

Keywords:

genetic algorithm, FIR filter, cascade structure of digital filter, standard deviation, piecewise-linear function

Abstract

The object of research is the process of digital signal processing. The subject of research is methods of synthesis of digital filters with a finite impulse response based on a genetic algorithm. Digital filtering is one of the tasks of digital signal processing. FIR filters are always stable and provide a constant group delay. There are various methods for synthesizing digital filters, but they are all aimed at synthesizing filters with a direct structure.

One of the most problematic areas of a digital filter with a direct structure in digital processing is the high sensitivity of the filter characteristics to inaccuracies in setting the filter coefficients. Genetic algorithm-based filter synthesis methods use an ideal filter as the approximated filter. This approach has a number of disadvantages: it complicates the search for an optimal solution; computation time increases.

The study used random search method, which is the basis of genetic algorithm (used for solving optimization problems); theory of digital filtering in filter analysis; numerical methods for modeling in a Python program.

Prepared synthesis method FIR filter with the cascade structure, which is less sensitive to the effect of finite bit width. Computation time was reduced. This is due to the fact that the proposed method searches for the most suitable filter coefficients based on a genetic algorithm and has a number of features, in particular, it is proposed to use a piecewise-linear function as an approximated amplitude-frequency response.

This makes it possible to reduce the number of populations of the genetic algorithm when searching for a solution. The synthesis of an FIR filter with a cascade structure based on a genetic algorithm showed that for a 24-order filter it took about 30–40 generations to get the filter parameters close to the optimal values. In comparison with classical methods of filter synthesis, the following advantages are provided: calculations of the coefficients of a filter with a cascade structure directly, the possibility of optimizing coefficients with limited bit depth.

Author Biographies

Ruslan Petrosian, Zhytomyr Polytechnic State University

Senior Lecturer

Department of Computer Science

Vladyslav Chukhov, Zhytomyr Polytechnic State University

PhD, Аssociate Professor

Department of Biomedical Engineering and Telecommunications

References

  1. Zubarev, Yu. B., Vityazev, V. V., Dvorkovich, V. P. (1999). Tsifrovaya obrabotka signalov – informatika realnogo vremeni. Tsifrovaya obrabotka signalov, 1, 5–17.
  2. Mitchell, M. (1998). An Introduction to Genetic Algorithms. London: MIT Press, 158. doi: http://doi.org/10.7551/mitpress/3927.001.0001
  3. Mutingi, M., Mbohwa, C. (2017). Grouping Genetic Algorithms. Advances and Applications. Switzerland: Springer International Publishing, 243. doi: http://doi.org/10.1007/978-3-319-44394-2
  4. Rabiner, L. (1978). Teoriya i primenenie tsifrovoy obrabotki signalov. Moscow: Izdatelstvo “Mir”, 848.
  5. Proakis, J., Manolakis, D. (2013). Digital Signal Processing. London: Pearson, 1019.
  6. Yukhimenko, B., Gulyaeva, N. (2018). Metody optimizatsii i issledovaniya operatsiy. Kyiv: Izdatelstvo «Feniks», 204.
  7. Thakare, V. V., Sahu, R. K. (2015). A Genetic Algorithm for Optimization of MSE & Ripples in Linear Phase Low Pass FIR Filter & Also Compare with Cosine Window Techniques. International Journals Digital Communication and Analog Signals, 1, 9–15.
  8. Sahu, R. K., Thakare, V. V. (2015). Comparative Designing of Optimal FIR Filter using Parks-McClellan & Genetic Algorithm. International Journal of Computer & Communication Engineering Research, 3, 46–49. Available at: http://www.ijcaonline.ijccer.org/index.php/ojs/article/download/162/77
  9. Karaboğa, N., Çetinkaya, B. (2004). Optimal design of minimum phase digital fir filters by using genetic algorithm. 3rd International Conference on Electrical and Electronics Engineering, 176–179. Available at: https://www.emo.org.tr/ekler/cf9d6bd14a20958_ek.pdf
  10. Solonina, A. I. (2018). Tsifrovaya obrabotka signalov v zerkale MATLAB. Saint Petersburg: Izdatelstvo “BKHV”, 560.
  11. Cheng, J. R., Gen M. (2020). Parallel Genetic Algorithms with GPU Computing. Intechopen, 26. doi: http://doi.org/10.5772/intechopen.89152

Downloads

Published

2021-07-31

How to Cite

Petrosian, R., Chukhov, V., & Petrosian, A. . (2021). Development of a method for synthesis the FIR filters with a cascade structure based on genetic algorithm. Technology Audit and Production Reserves, 4(2(60), 6–11. https://doi.org/10.15587/2706-5448.2021.237271

Issue

Vol. 4 No. 2(60) (2021): Information and control systems

Section

Information Technologies: Original Research

License

Copyright (c) 2021 Ruslan Petrosian, Vladyslav Chukhov, Arsen Petrosian

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.