Skip to main content

Improving Enclosure of Interval Scalar Projection Operation

  • Conference paper
  • First Online:
  • 506 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10693))

Abstract

We introduce interval scalar projection operation with tight interval enclosure. Our approach relies on the solution to non-convex optimization problem. We present an improved algorithm for computing interval scalar projection for 2-dimensional box intervals and compare to a simple algorithm based on natural interval extension method. Applications include automated verification of properties of geometric algorithms and computing Voronoi diagrams over inexact input data.

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

Buying options

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 EPUB and 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

Learn about institutional subscriptions

References

  1. Aurenhammer, F.: Voronoi diagrams - a survey of a fundamental geometric data structure. ACM Comput. Surv. 23(3), 345–405 (1991)

    Article  Google Scholar 

  2. Bauschke, H.H., Borwein, J.M.: Dykstra’s alternating projection algorithm for two sets. J. Approx. Theory 79(3), 418–443 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  3. Carrizosa, E., Hansen, P., Messine, F.: Improving interval analysis bounds by translations. J. Global Optim. 29(2), 157–172 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  4. Cheng, R., Xie, X., Yiu, M.L., Chen, J., Sun, L.: UV-diagram: a Voronoi diagram for uncertain data. In: 2010 IEEE 26th International Conference on Data Engineering (ICDE), pp. 796–807. IEEE (2010)

    Google Scholar 

  5. Daumas, M., Lester, D., Munoz, C.: Verified real number calculations: a library for interval arithmetic. IEEE Trans. Comput. 58(2), 226–237 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  6. Dykstra, R.L.: An algorithm for restricted least squares regression. J. Am. Stat. Assoc. 78(384), 837–842 (1983)

    Article  MathSciNet  MATH  Google Scholar 

  7. Khanban, A.A.: Basic algorithms in computational geometry with imprecise input. Ph.D. thesis, University of London (2005)

    Google Scholar 

  8. Moore, R.E., Kearfott, R.B., Cloud, M.J.: Introduction to Interval Analysis. SIAM, Philadelphia (2009)

    Book  MATH  Google Scholar 

  9. Nedialkov, N.S., Kreinovich, V., Starks, S.A.: Interval arithmetic, affine arithmetic, Taylor series methods: why, what next? Numer. Algorithms 37(1), 325–336 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  10. Neumaier, A.: Taylor forms–use and limits. Reliable Comput. 9(1), 43–79 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  11. Neumaier, A.: Improving interval enclosures. Reliable Comput. (2009)

    Google Scholar 

  12. Owre, S., Rushby, J.M., Shankar, N.: PVS: a prototype verification system. In: Kapur, D. (ed.) CADE 1992. LNCS, vol. 607, pp. 748–752. Springer, Heidelberg (1992). https://doi.org/10.1007/3-540-55602-8_217

    Google Scholar 

  13. Reem, D.: The geometric stability of Voronoi diagrams with respect to small changes of the sites. In: Proceedings of the Twenty-Seventh Annual Symposium on Computational Geometry, SoCG 2011, pp. 254–263. ACM (2011)

    Google Scholar 

  14. Seeger, A., Sossa, D.: Critical angles between two convex cones. TOP 24(1), 44–87 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  15. Shakhnarovich, G., Darrell, T., Indyk, P.: Nearest-Neighbor Methods in Learning and Vision: Theory and Practice. Neural Information Processing. The MIT Press, Cambridge (2006)

    Google Scholar 

  16. Stoer, J., Witzgall, C.: Convexity and Optimization in Finite Dimensions I, vol. 163. Springer Science & Business Media, Heidelberg (2012)

    MATH  Google Scholar 

  17. Stolfi, J., De Figueiredo, L.: An introduction to affine arithmetic. Trends Appl. Comput. Math. 4(3), 297–312 (2003)

    MathSciNet  MATH  Google Scholar 

  18. Tenenhaus, M.: Canonical analysis of two convex polyhedral cones and applications. Psychometrika 53(4), 503–524 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  19. Wiedijk, F.: The Seventeen Provers of the World: Foreword by Dana S. Scott, vol. 3600. Springer, Heidelberg (2006)

    MATH  Google Scholar 

  20. Worley, S.: A cellular texture basis function. In: Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH 1996, pp. 291–294. ACM (1996)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tomasz Dobrowolski .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Dobrowolski, T. (2017). Improving Enclosure of Interval Scalar Projection Operation. In: Blömer, J., Kotsireas, I., Kutsia, T., Simos, D. (eds) Mathematical Aspects of Computer and Information Sciences. MACIS 2017. Lecture Notes in Computer Science(), vol 10693. Springer, Cham. https://doi.org/10.1007/978-3-319-72453-9_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-72453-9_10

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72452-2

  • Online ISBN: 978-3-319-72453-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics