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Application of Geometric Differential Evolution Algorithm to Design Minimal Phase Digital Filters with Atypical Characteristics for Their Hardware or Software Implementation

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Book cover Artificial Intelligence and Soft Computing (ICAISC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7895))

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Abstract

In this paper, the application of a geometric differential evolution algorithm to design minimal phase digital filters with atypical characteristics is presented. Owing to the method proposed, we can design digital filters for any numerical systems in dedicated hardware implementation. Moreover, with the use of a geometric differential evolution algorithm, we can create digital filters for hardware and/or software implementation using the same design algorithm. In the paper, a design of two digital filters in the Q.15 numerical format (for hardware realization) and in the real number numerical format (for software realization) is presented. The results obtained using the proposed method are better than the results obtained with the use of the other methods.

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References

  1. Slowik, A.: Application of Evolutionary Algorithm to Design of Minimal Phase Digital Filters with Non-Standard Amplitude Characteristics and Finite Bits Word Length. Bulletin of The Polish Academy of Science - Technical Science 59(2), 125–135 (2011), doi:10.2478/v10175-011-0016-z

    Google Scholar 

  2. Orfanidis, S.J.: Introduction to Signal Processing. Prentice-Hall (1995)

    Google Scholar 

  3. Ding, H., Lu, J., Qiu, X., Xu, B.: Anadaptive speech enhancement method for siren noise cancellation. Applied Acoustics 65, 385–399 (2004)

    Article  Google Scholar 

  4. Michalewicz, Z.: Genetic algorithms + data structures = evolution programs. Springer, Heidelberg (1992)

    Book  MATH  Google Scholar 

  5. Takaaki, N., Takahiko, K., Keiichiro, Y.: Deterministic Genetic Algorithm. Papers of Technical Meeting on Industrial Instrumentation and Control, IEE Japan, pp. 33-36 (2003)

    Google Scholar 

  6. Słowik, A., Białko, M.: Modified Version of Roulette Selection for Evolution Algorithms – The Fan Selection. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 474–479. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  7. Słowik, A.: Steering of Balance between Exploration and Exploitation Properties of Evolutionary Algorithms - Mix Selection. In: Rutkowski, L., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2010, Part II. LNCS (LNAI), vol. 6114, pp. 213–220. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  8. Dorigo, M., Maniezzo, V., Colorni, A.: Ant System: Optimization by a colony of cooperating agents. IEEE Transactions on SMC-B 26(1), 29–41 (1996)

    Google Scholar 

  9. Bilchev, G., Parmee, I.C.: The ant colony metaphor for searching continous design spaces. In: Fogarty, T.C. (ed.) AISB-WS 1995. LNCS, vol. 993, pp. 25–39. Springer, Heidelberg (1995)

    Chapter  Google Scholar 

  10. Eberhart, R.C.: Kennedy J.A.: New optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micromachine and Human Science, Nagoya, Japan, pp. 39–43 (1995)

    Google Scholar 

  11. Kennedy, J., Eberhart, R.C.: Particle swarm optimization. In: Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, pp. 1942–1948 (1995)

    Google Scholar 

  12. Kennedy, J., Eberhart, R.C., Shi, Y.: Swarm intelligence. Morgan Kaufmann Publishers, San Francisco (2001)

    Google Scholar 

  13. Slowik, A.: Hybridization of Evolutionary Algorithm with Yule Walker Method to Design Minimal Phase Digital Filters with Arbitrary Amplitude Characteristics. In: Corchado, E., Kurzyński, M., Woźniak, M. (eds.) HAIS 2011, Part I. LNCS (LNAI), vol. 6678, pp. 67–74. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  14. Karaboga, N., Cetinkaya, B.: Design of minimum phase digital IIR filters by using genetic algorithm. In: Proc. 6th Nordic Signal Processing Symposium 1, CD-ROM (2004)

    Google Scholar 

  15. Nakamoto, M., Yoshiya, T., Hinamoto, T.: Finite wordlength design for IIR digital filters based on the modified least-square criterion in the frequency domain. In: Int. Symposium on Intelligent Signal Processing and Communication Systems, ISPACS, vol. 1, pp. 462–465 (2007)

    Google Scholar 

  16. Baicher, G.S.: Optimization of finite word length coefficient IIR digital filters through genetic algorithms a comparative study. In: Jiao, L., Wang, L., Gao, X.-b., Liu, J., Wu, F. (eds.) ICNC 2006. LNCS, vol. 4222, pp. 641–650. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  17. Karaboga, N., Cetinkaya, B.: Performance comparison of genetic algorithm based design methods of digital filters with optimal magnitude response and minimum phase. In: 46th IEEE Midwest Symposium on Circuits and Systems 1, CD-ROM (2003)

    Google Scholar 

  18. Moraglio, A., Togelius, J.: Geometric differential evolution. In: Proceeding GECCO 2009 Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation, pp. 1705–1712 (2009)

    Google Scholar 

  19. Storn, R., Price, K.V.: Differential evolution a simple and efficient heuristic for global optimization over continuous spaces. Global Optimization 11, 341–359 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  20. Price, K.V.: An Introduction to Differential Evolution. New Ideas in Optimization, 79–108 (1999)

    Google Scholar 

  21. Lyons, R.: Introduction to Digital Signal Processing. WKL, Warsaw (2000) (in polish)

    Google Scholar 

  22. Bocewicz, G., Wójcik, R., Banaszak, Z.: Agvs distributed control subject to imprecise operation times. In: Nguyen, N.T., Jo, G.-S., Howlett, R.J., Jain, L.C. (eds.) KES-AMSTA 2008. LNCS (LNAI), vol. 4953, pp. 421–430. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  23. Bocewicz, G., Banaszak, Z.: Declarative modeling of multimodal cyclic processes. In: Golinska, P., Fertsch, M., Marx-Gomez, J. (eds.) Information Technologies in Environmental Engineering. Environmental Science and Engineering - Environmental Engineering, vol. 3, pp. 551–568. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

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Authors and Affiliations

  1. Department of Electronics and Computer Science, Koszalin University of Technology, Sniadeckich 2 Street, 75-453, Koszalin, Poland

    Adam Slowik

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  1. Adam Slowik
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Michiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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Slowik, A. (2013). Application of Geometric Differential Evolution Algorithm to Design Minimal Phase Digital Filters with Atypical Characteristics for Their Hardware or Software Implementation. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7895. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38610-7_7

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  • DOI: https://doi.org/10.1007/978-3-642-38610-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38609-1

  • Online ISBN: 978-3-642-38610-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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