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Hybridization of Evolutionary Algorithm with Yule Walker Method to Design Minimal Phase Digital Filters with Arbitrary Amplitude Characteristics

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Hybrid Artificial Intelligent Systems (HAIS 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6678))

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Abstract

In this paper a method of design minimal phase digital filters with arbitrary amplitude characteristics is presented. The filters designed using proposed method can be directly implemented in the hardware. Filter coefficients obtained using proposed method are immune on rounding error. Because these coefficients are created in required bit word length (based on numerical format which is used in given DSP system). The proposed method is based on connection of evolutionary algorithm and Yule Walker method. Due to this hybridization, digital filters are designed faster (than using only evolutionary algorithm) and possess much better properties (then using only Yule Walker method). Digital filters obtained using proposed method are ready to be implemented in DSP system without any additional errors. The four minimal phase digital filters (with coefficients in Q.15 format) and with arbitrary amplitude characteristics are designed using proposed method. The results obtained using proposed method are compared with results obtained using other techniques taken from literature.

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References

  1. 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, Egypt (2003)

    Google Scholar 

  2. Venkata, N.D., Evans, B.L.: Optimal Design of Real and Complex Minimum Phase Digital FIR Filters. In: IEEE International Conference on Acoustics, Speech, and Signal Processing, vol. 3, pp. 1145–1148 (1999)

    Google Scholar 

  3. Slowik, A., Bialko, M.: Design and Optimization of IIR Digital Filters with Non-standard Characteristics Using Continuous Ant Colony Optimization Algorithm. In: Darzentas, J., Vouros, G.A., Vosinakis, S., Arnellos, A. (eds.) SETN 2008. LNCS (LNAI), vol. 5138, pp. 395–400. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

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

    Google Scholar 

  5. 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 

  6. TMS320C54x DSP Library Programmers Reference, Texas Instruments, Dallas, TX, SPRU422b (2001)

    Google Scholar 

  7. TMS320C55x DSP Library Programmers Reference, Texas Instruments, Dallas, TX, SPRU422F (2002)

    Google Scholar 

  8. Gan, W.-S., Kuo, S.M.: Teaching DSP Software Development: From Design to Fixed-Point Implementations. IEEE Transactions on Education 49(1) (2006)

    Google Scholar 

  9. Lyons, R.: Introduction to digital signal processing. In: WKL, Warsaw (2000)

    Google Scholar 

  10. 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 

  11. Karaboga, N., Cetinkaya, B.: Design of Minimum Phase Digital IIR Filters by Using Genetic Algorithm. In: Proceedings of the 6th Nordic Signal Processing Symposium - NORSIG 2004, Espoo, Finland, June 9-11 (2004)

    Google Scholar 

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

    Book  MATH  Google Scholar 

  13. Goldberg, D.E.: Genetic algorithms in search, optimization, and machine learning. Addison-Wesley Publishing Company Inc., New York (1989)

    MATH  Google Scholar 

  14. Derrac, J., García, S., Herrera, F.: A first study on the use of coevolutionary algorithms for instance and feature selection. In: Corchado, E., Wu, X., Oja, E., Herrero, Á., Baruque, B. (eds.) HAIS 2009. LNCS, vol. 5572, pp. 557–564. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  15. Corchado, E., Abraham, A., Ferreira de Carvalho, A.C.P.L.: Hybrid intelligent algorithms and applications. Information Science 180(14), 2633–2634 (2010)

    Article  MathSciNet  Google Scholar 

  16. Wozniak, M., Zmyslony, M.: Designing Fusers on the Basis of Discriminants – Evolutionary and Neural Methods of Training. In: Graña Romay, M., Corchado, E., Garcia Sebastian, M.T. (eds.) HAIS 2010. LNCS (LNAI), vol. 6076, pp. 590–597. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  17. Abraham, A., Corchado, E., Corchado, J.M.: Hybrid learning machines. Neurocomputing 72(13-15), 2729–2730 (2009)

    Article  Google Scholar 

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Slowik, A. (2011). 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) Hybrid Artificial Intelligent Systems. HAIS 2011. Lecture Notes in Computer Science(), vol 6678. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21219-2_10

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  • DOI: https://doi.org/10.1007/978-3-642-21219-2_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21218-5

  • Online ISBN: 978-3-642-21219-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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