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Reseach Article

A Method of Curve Fitting by Recurrent Fractal Interpolation

Published on March 2012 by Bhagwati Prasad, Bani Singh, Kuldip Katiyar
International Conference in Computational Intelligence
Foundation of Computer Science USA
ICCIA - Number 3
March 2012
Authors: Bhagwati Prasad, Bani Singh, Kuldip Katiyar
e6f5b231-3a92-4b73-bff0-ceccf960a114

Bhagwati Prasad, Bani Singh, Kuldip Katiyar . A Method of Curve Fitting by Recurrent Fractal Interpolation. International Conference in Computational Intelligence. ICCIA, 3 (March 2012), 5-8.

@article{
author = { Bhagwati Prasad, Bani Singh, Kuldip Katiyar },
title = { A Method of Curve Fitting by Recurrent Fractal Interpolation },
journal = { International Conference in Computational Intelligence },
issue_date = { March 2012 },
volume = { ICCIA },
number = { 3 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 5-8 },
numpages = 4,
url = { /proceedings/iccia/number3/5107-1019/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference in Computational Intelligence
%A Bhagwati Prasad
%A Bani Singh
%A Kuldip Katiyar
%T A Method of Curve Fitting by Recurrent Fractal Interpolation
%J International Conference in Computational Intelligence
%@ 0975-8887
%V ICCIA
%N 3
%P 5-8
%D 2012
%I International Journal of Computer Applications
Abstract

The real world objects are too irregular to be modeled with the help of traditional interpolation methods. M. F. Barnsley in 1986 proposed the concept of fractal interpolation function (FIF) using iterated function systems (IFS) to describe such real world data. In many cases these data sets represent a curve rather than a function i.e. the data points are not linearly ordered with their abscissa and self affinity is not satisfied in the whole range. The recurrent fractal interpolation function (RFIF) has a role to play in such cases. The purpose of this paper is to apply recurrent fractal interpolation function to fit the piecewise self affine data.

References
  1. Barnsley, M. F. 1986. Fractal functions and interpolation, Constr. Approx. 2, 303-329.
  2. Barnsley, M. F., John H. Elton, D. and Hardin, P. 1989. Recurrent iterated function systems in Fractal Approximation, Constr. Approx. 5, 3–31.
  3. Barnsley, M. F. 1993. Fractals Everywhere, 2nd edition, Revised with the assistance of and a foreword by Hawley Rising, III. Boston MA, Academic Press Professional.
  4. Barnsley, M. F., Hutchinson, J. E. and Stenflo, O. 2008. Fractals with partial self similarity, Adv. Math 218(6), 2051-88.
  5. Cochran, W. O., Hart, J. C. and Flynn, P. J. 1998. On approximating rough curves with fractal functions. Proc. Graphics Interface. 1, 65–72.
  6. Dalla, L. and Drakopoulos, V. 1999. On the parameter identification problem in the plane and the polar fractal interpolation functions. J. Approx. Theory 101, 290–303.
  7. Guerin, E., Tosan, E. and Baskurt, A. 2000. Fractal coding of shapes based on a projected IFS model. In: ICIP, 2, IEEE Computer Society Press, Los Alamitos, 203–206.
  8. Guerin, E., Tosan, E. and Baskurt, A. 2001. A fractal approximation of curves. Fractals 9, 95–103.
  9. Hutchinson, J. E. 1981. Fractals and self similarity, Indiana Univ. Math. J. 30, 713-747.
  10. Mandelbrot, B. B. 1977. The Fractal Geometry of Nature, Updated and Augmented, International Business Machines, Thomas J. Watson Research Center, H. Freeman And Company, New York.
  11. Mazel, D. S. and Hayes, M. H. 1991. Hidden-variable fractal interpolation of discrete sequences. Proc. Int. Conf. ASSP.1, 3393–3396
  12. Mazel, D. S. and Hayes, M. H. 1992. Using iterated function systems to model discrete sequences. IEEE Trans. Signal Process. 40, 1724–1734
  13. Mazel, D. S. 1994. Representation of discrete sequences with three-dimensional iterated function systems. IEEE Trans. Signal Processing 42, 3269–3271.
  14. Manousopoulos, P., Drakopoulos, V. and Theoharis, T. 2008. Curve fitting by fractal interpolation. Trans. Comput. Sci. 1, 85–103.
  15. Navascues, M. A. and Sebastian, M. V. 2004. Fitting curves by fractal interpolation: An application to the quantification of cognitive brain processes. In: Novak, M.M. (ed.) Thinking in patterns: Fractals and related phenomena in nature, World Scientific, Singapore, 143–154.
  16. Prasad, B. and Katiyar, K. 2011. Fractals via ishikawa iteration, CCIS, Springer Berlin Heidelberg, 140(2), 197-203.
  17. Priceand, J. R. and Hayes, M. H., 1998. Resampling and reconstructing with fractal interpolation functions, IEEE Signal Process. Letters, 5, 228-230.
  18. Singh, S. L., Prasad, B. and Kumar, A. 2009. Fractals via iterated functions and multifunctions. Chaos, Solitons and Fractals 39, 1224-1231.
  19. Uemura, S., Haseyama, M., and Kitajima, H. 2002. Efficient contour shape description by using fractal interpolation functions. IEEE Proc. ICIP. 1, 485–488.
Index Terms

Computer Science
Information Sciences

Keywords

Fractal interpolation Recurrent fractal interpolation function Piecewise self affine function curve fitting.