Skip to main content

Constrained 2D Data Interpolation Using Rational Cubic Fractal Functions

  • Conference paper
  • First Online:
Mathematical Analysis and its Applications

Part of the book series: Springer Proceedings in Mathematics & Statistics ((PROMS,volume 143))

Abstract

In this paper, we construct the \(\mathscr {C}^1\)-rational cubic fractal interpolation function (RCFIF) and its application in preserving the constrained nature of a given data set. The \(\mathscr {C}^1\)-RCFIF is the fractal design of the traditional rational cubic interpolant of the form \(\frac{p_i(\theta )}{q_i(\theta )}\), where \(p_i(\theta )\) and \(q_i(\theta )\) are the cubic polynomials with three tension parameters. We derive the uniform error bound between the RCFIF with the original function in \(\mathscr {C}^3[x_1,x_n]\). When the data set is constrained between two piecewise straight lines, we deduce the sufficient conditions on the parameters of the RCFIF so that it lies between those two lines. Numerical examples are given to support that our method is interactive and smooth.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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

References

  1. Abbas, M., Jamal, E., Ali, J.M.: Shape preserving constrained data visualization using spline functions. Int. J. Appl. Math. Stat. 29(5), 34–50 (2012)

    MathSciNet  Google Scholar 

  2. Abbas., M, Majid., A.A, Awang., M.N.H, Ali, J.M.: Local convexity shape-preserving data visualization by spline function. ISRN Math. Anal. 2012(Article ID: 174048), 1–14 (2012)

    Google Scholar 

  3. Awang, M.N.H., Abbas. M., Majid, A.A., Ali, J.M.: Data visualization for constrained data using \(\cal C^2\) rational cubic spline. In: Proceedings of the World Congress on Engineering and Computer Science, vol. 1 (2013)

    Google Scholar 

  4. Barnsley, M.F.: Fractal functions and interpolation. Constr. Approx. 2, 303–329 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  5. Barnsley, M.F., Harrington, A.N.: The calculus of fractal interpolation functions. J. Approx. Theory 57(1), 14–34 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  6. Chand, A.K.B., Kapoor, G.P.: Generalized cubic spline fractal interpolation functions. SIAM J. Numer. Anal. 44(2), 655–676 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  7. Chand, A.K.B., Navascués, M.A.: Generalized Hermite fractal interpolation. Rev. R. Acad. Cienc. Zaragoza 64(2), 107–120 (2009)

    MATH  Google Scholar 

  8. Chand, A.K.B., Viswanathan, P.: Cubic Hermite and cubic spline fractal interpolation functions. AIP Conf. Proc. 1479, 1467–1470 (2012)

    Article  MATH  Google Scholar 

  9. Chand, A.K.B., Viswanathan, P.: A constructive approach to cubic Hermite fractal interpolation function and its constrained aspects. BIT Numer. Math. 53(4), 841–865 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  10. Chand, A.K.B., Vijender, N., Agarwal, R.P.: Rational iterated function system for positive/monotonic shape preservation. Adv. Differ. Eqn. 2014(30), 1–19 (2014)

    Google Scholar 

  11. Chand, A.K.B., Vijender, N., Navascués, M.A.: Shape preservation of scientific data through rational fractal splines. Calcolo 51(2), 329–362 (2014)

    Article  MathSciNet  Google Scholar 

  12. Dalla, L., Drakapoulos, V.: On the parameter identification problem in the plane and polar fractal interpolation functions. J. Approx. Theory 101, 289–302 (1999)

    Article  MathSciNet  MATH  Google Scholar 

  13. Duan, Q., Xu, G., Liu, A., Wang, X., Cheng, F.: Constrained interpolation using rational cubic spline with linear denominators. Korean J. Comput. Appl. Math. 6, 203–215 (1999)

    MathSciNet  MATH  Google Scholar 

  14. Duan, Q., Wang, L., Twizell, E.H.: A new \(\cal C^2\) rational interpolation based on function values and constrained control of the interpolant curves. J. Appl. Math. Comput. 61, 311–322 (2005)

    Google Scholar 

  15. Gregory, J.A., Delbourgo, R.: Shape preserving piecewise rational interpolation. SIAM J. Stat. Comput. 6(4), 967–976 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  16. Hussian, M.Z., Sarfraz, M., Hussain, M.: Scientific data visualization with shape preserving \(\cal C^1\)-rational cubic interpolation. Eur. J. Pure Appl. Math. 3(2), 194–212 (2010)

    Google Scholar 

  17. Sarfraz, M., Hussain, M.Z.: Data visualization using rational spline interpolation. J. Comp. Appl. Math 189, 513–525 (2006)

    Google Scholar 

  18. Tahira, S.S., Sarfraz, M., Hussain., M.Z.: Shape preserving constrained data visualization using rational functions. J. Prime Res. Math. 7, 35–51 (2011)

    Google Scholar 

  19. Viswanathan, P., Chand, A.K.B.: A \(\cal C^1\)-rational cubic fractal interpolation function: convergence and associated parameter identification problem. Acta. Appl. Math. 136(1), 19–41 (2015)

    Google Scholar 

  20. Viswanathan, P., Chand, A.K.B., Navascués, M.A.: Fractal perturbation preserving fundamental shapes: Bounds on the scale factors. J. Math. Anal. Appl. 419(2), 804–817 (2014)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgments

The first author is thankful to the Department of Science & Technology, India for the SERC DST Project No. SR/S4/MS: 694/10.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. K. B. Chand .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer India

About this paper

Cite this paper

Chand, A.K.B., Tyada, K.R. (2015). Constrained 2D Data Interpolation Using Rational Cubic Fractal Functions. In: Agrawal, P., Mohapatra, R., Singh, U., Srivastava, H. (eds) Mathematical Analysis and its Applications. Springer Proceedings in Mathematics & Statistics, vol 143. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2485-3_49

Download citation

Publish with us

Policies and ethics