Skip to main content
SpringerLink
Log in

Data Extrapolation and Decision Making via Method of Hurwitz-Radon Matrices

  • Conference paper
Computational Collective Intelligence. Technologies and Applications (ICCCI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6922))

Included in the following conference series:

Abstract

Computational Collective Intelligence needs suitable methods of data extrapolation and decision making. Proposed method of Hurwitz-Radon Matrices (MHR) can be used in extrapolation and interpolation of curves in the plane. For example quotations from the Stock Exchange, the market prices or rate of a currency form a curve. This paper contains the way of data anticipation and extrapolation via MHR method and decision making: to buy or not, to sell or not. Proposed method is based on a family of Hurwitz-Radon (HR) matrices. The matrices are skew-symmetric and possess columns composed of orthogonal vectors. The operator of Hurwitz-Radon (OHR), built from these matrices, is described. Two-dimensional data are represented by the set of curve points. It is shown how to create the orthogonal and discrete OHR and how to use it in a process of data foreseeing and extrapolation. MHR method is interpolating and extrapolating the curve point by point without using any formula or function.

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

Access this chapter

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 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Brachman, R.J., Levesque, H.J.: Knowledge Representation and Reasoning. Morgan Kaufman, San Francisco (2004)

    MATH  Google Scholar 

  2. Fagin, R., Halpern, J.Y., Moses, Y., Vardi, M.Y.: Reasoning About Knowledge. MIT Press, Cambridge (1995)

    MATH  Google Scholar 

  3. Straffin, P.D.: Game Theory and Strategy. Mathematical Association of America, Washington, D.C (1993)

    MATH  Google Scholar 

  4. Watson, J.: Strategy – An Introduction to Game Theory. University of California, San Diego (2002)

    Google Scholar 

  5. Markman, A.B.: Knowledge Representation. Lawrence Erlbaum Associates, Mahwah (1998)

    Google Scholar 

  6. Sowa, J.F.: Knowledge Representation: Logical, Philosophical and Computational Foundations. Brooks/Cole, New York (2000)

    Google Scholar 

  7. Soussen, C., Mohammad-Djafari, A.: Polygonal and Polyhedral Contour Reconstruction in Computed Tomography. IEEE Transactions on Image Processing 11(13), 1507–1523 (2004)

    Article  MathSciNet  Google Scholar 

  8. Tang, K.: Geometric Optimization Algorithms in Manufacturing. Computer – Aided Design & Applications 2(6), 747–757 (2005)

    Article  Google Scholar 

  9. Kozera, R.: Curve Modeling via Interpolation Based on Multidimensional Reduced Data. Silesian University of Technology Press, Gliwice (2004)

    Google Scholar 

  10. Dahlquist, G., Bjoerck, A.: Numerical Methods. Prentice Hall, New York (1974)

    Google Scholar 

  11. Ralston, A.: A First Course in Numerical Analysis. McGraw-Hill Book Company, New York (1965)

    MATH  Google Scholar 

  12. Eckmann, B.: Topology, Algebra, Analysis- Relations and Missing Links. Notices of the American Mathematical Society 5(46), 520–527 (1999)

    MathSciNet  MATH  Google Scholar 

  13. Citko, W., Jakóbczak, D., Sieńko, W.: On Hurwitz - Radon Matrices Based Signal Processing. In: Workshop Signal Processing at Poznan University of Technology (2005)

    Google Scholar 

  14. Tarokh, V., Jafarkhani, H., Calderbank, R.: Space-Time Block Codes from Orthogonal Designs. IEEE Transactions on Information Theory 5(45), 1456–1467 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  15. Sieńko, W., Citko, W., Wilamowski, B.: Hamiltonian Neural Nets as a Universal Signal Processor. In: 28th Annual Conference of the IEEE Industrial Electronics Society IECON (2002)

    Google Scholar 

  16. Sieńko, W., Citko, W.: Hamiltonian Neural Net Based Signal Processing. In: The International Conference on Signal and Electronic System ICSES (2002)

    Google Scholar 

  17. Jakóbczak, D.: 2D and 3D Image Modeling Using Hurwitz-Radon Matrices. Polish Journal of Environmental Studies 4A(16), 104–107 (2007)

    Google Scholar 

  18. Jakóbczak, D.: Shape Representation and Shape Coefficients via Method of Hurwitz-Radon Matrices. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (eds.) ICCVG 2010. LNCS, vol. 6374, pp. 411–419. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  19. Jakóbczak, D.: Curve Interpolation Using Hurwitz-Radon Matrices. Polish Journal of Environmental Studies 3B(18), 126–130 (2009)

    Google Scholar 

  20. Jakóbczak, D.: Application of Hurwitz-Radon Matrices in Shape Representation. In: Banaszak, Z., Świć, A. (eds.) Applied Computer Science: Modelling of Production Processes, vol. 1(6), pp. 63–74. Lublin University of Technology Press, Lublin (2010)

    Google Scholar 

  21. Jakóbczak, D.: Object Modeling Using Method of Hurwitz-Radon Matrices of Rank k. In: Wolski, W., Borawski, M. (eds.) Computer Graphics: Selected Issues, pp. 79–90. University of Szczecin Press, Szczecin (2010)

    Google Scholar 

  22. Jakóbczak, D.: Implementation of Hurwitz-Radon Matrices in Shape Representation. In: Choraś, R.S. (ed.) Image Processing and Communications Challenges 2. Advances in Intelligent and Soft Computing, vol. 84, pp. 39–50. Springer, Heidelberg (2010)

    Chapter  Google Scholar 

  23. Chang, F.-C., Huang, H.-C.: A Refactoring Method for Cache-Efficient Swarm Intelligence Algorithms. Information Sciences (2010), doi:10.1016/j.ins.2010.02.025

    Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Dariusz Jakóbczak

Authors
  1. Dariusz Jakóbczak
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Gdynia Maritime University, Morska 81-87, 81-225, Gdynia, Poland

    Piotr Jędrzejowicz

  2. Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. University of Information Technology Vietnam, Km 20, Xa lo Ha Noi, Linh Trung, Thu Duc, 848, HCM City, Vietnam

    Kiem Hoang

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jakóbczak, D. (2011). Data Extrapolation and Decision Making via Method of Hurwitz-Radon Matrices. In: Jędrzejowicz, P., Nguyen, N.T., Hoang, K. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2011. Lecture Notes in Computer Science(), vol 6922. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23935-9_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-23935-9_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23934-2

  • Online ISBN: 978-3-642-23935-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation