Skip to main content
SpringerLink
Log in
Book cover

International Conference on Natural Computation

ICNC 2006: Advances in Natural Computation pp 641–650Cite as

Optimization of Finite Word Length Coefficient IIR Digital Filters Through Genetic Algorithms – A Comparative Study

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4222))

Abstract

This paper considers the specific issues relating to finite word length (FWL) coefficient constraints for the case of infinite impulse response (IIR) digital filters. Due to the feedback nature of recursive filters, stability issues are an important factor in their design and are discussed in some detail. Some previously reported work on the optimization of FWL coefficients for IIR filters is also discussed. Extensive range of filter types and structures of IIR filters and their optimization using genetic algorithms is investigated and reported. Finally, comparative tests were conducted using the simple hill climber optimization techniques for a selection of filters.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baicher, G.S., Taylor, M., Rowlands, H.: A comparative study of finite word length coefficient optimization of FIR digital filters. In: Wang, L., Chen, K., S. Ong, Y. (eds.) ICNC 2005. LNCS, vol. 3612, pp. 877–882. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  2. Kaiser, J.F.: Some practical considerations in the realization of linear digital filters. In: Proceedings of the 3rd Annual Allerton conference on Circuit System Theory, pp. 621–633 (1965)

    Google Scholar 

  3. Parks, T.W., Burrus, C.S.: Digital Filter Design. John Wiley, New York (1987)

    MATH  Google Scholar 

  4. Oppenheim, A.V., Shaffer, R.W.: Discrete-time Signal Processing. Prentice-Hall, Englewood Cliffs (1989)

    MATH  Google Scholar 

  5. Jackson, L.B.: Digital filters and signal processing. Kluwer, Boston (1989)

    Google Scholar 

  6. Roberts, R., Mullis, C.T.: Digital Signal Processing. Addison-Wesley, Reading (1987)

    MATH  Google Scholar 

  7. Gray, A.H., Markel, J.D.: Digital Lattice and Ladder filter synthesis. IEEE Transactions on audio and electroacoustics 21, 491–500 (1973)

    Article  MathSciNet  Google Scholar 

  8. Fettweis, A.: Wave digital lattice filters. International Journal on Circuit theory application 2, 203–211 (1974)

    Article  Google Scholar 

  9. Dempster, A.G., Macleod, M.D.: Multiplier blocks and the complexity of IIR structures. IEE Electronics letters 30, 1841–1842 (1994)

    Article  Google Scholar 

  10. Ifeachor, E.C., Jervis, B.W.: Digital Signal Processing: A practical approach. Addison-Wesley publishing, Wokingham (1993)

    Google Scholar 

  11. Mitra, S.K.: Digital Signal Processing – a computer based approach. McGraw-Hill, New York (1998)

    Google Scholar 

  12. Wilson, P.B., Macleod, M.D.: Low implementation cost IIR digital filter design using genetic algorithms. In: Proceedings of the workshop on Natural algorithms in signal processing, Chelmsford, November 1993, vol. 1, pp. 4/1–4/8 (1993)

    Google Scholar 

  13. Harris, S.P., Ifeachor, E.C.: Automatic design of frequency sampling filters by hybrid genetic algorithm techniques. IEEE Transactions on Signal Processing 46(12), 3304–3314 (1998)

    Article  Google Scholar 

  14. Arslan, T., Horrocks, D.H.: A genetic algorithm for the design of finite word length arbitrary response cascaded IIR digital filters. In: Proceedings of IEE International conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA 1995), pp. 276–281 (1995)

    Google Scholar 

  15. Chipperfield, A., Fleming, P., Pohlheim, H., Fonseca, C.: Genetic Algorithm Toolbox for use with MATLAB. Dept. of Automatic Control and Sys. Eng., University of Sheffield, ver. 1.2 (1993)

    Google Scholar 

  16. Baicher, G.S.: Towards Optimisation of Digital Filters and Multirate Filter Banks through Genetic Algorithms, PhD Thesis, University of Wales, Newport, South Wales, UK (2003)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Engineering, Newport Business School, University of Wales Newport, Allt-yr-yn Campus, P.O.Box 180, NP20 5XR, Newport, South Wales, U.K.

    Gurvinder S. Baicher

Authors
  1. Gurvinder S. Baicher
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Life Science Research Center, School of Electronic Engineering, Xidian University, 710071, Xi’an, Shaanxi, China

    Licheng Jiao

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Block S1, Nanyang Avenue, 639798, Singapore

    Lipo Wang

  3. School of Electronic Engineering, Xidian Univ., P.O. Box, 710071, Xi’an, P.R. China

    Xinbo Gao

  4. College of Mathematics and Information Science, Hebei Normal University, 050016, Shijiazhuang, Hebei, P.R. China

    Jing Liu

  5. Multi-Agent Systems Lab,Department of Computer Science, University of Science and Technology of China, 230026, Hefei, China

    Feng Wu

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Baicher, G.S. (2006). Optimization of Finite Word Length Coefficient IIR Digital Filters Through Genetic Algorithms – A Comparative Study. In: Jiao, L., Wang, L., Gao, X., Liu, J., Wu, F. (eds) Advances in Natural Computation. ICNC 2006. Lecture Notes in Computer Science, vol 4222. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11881223_79

Download citation

  • DOI: https://doi.org/10.1007/11881223_79

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45907-1

  • Online ISBN: 978-3-540-45909-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation