Abstract
We have investigated the Cantor set from the perspective of fractals and box-counting dimension. Cantor sets can be constructed geometrically by continuous removal of a portion of the closed unit interval [0, 1] infinitely. The set of points remained in the unit interval after this removal process is over is called the Cantor set. The dimension of such a set is not an integer value. In fact, it has a ‘fractional’ dimension, making it by definition a fractal. The Cantor set is an example of an uncountable set with measure zero and has potential applications in various branches of mathematics such as topology, measure theory, dynamical systems and fractal geometry. In this paper, we have provided three types of generalization of the Cantor set depending on the process of removal. Also, we have discussed some characteristics of the fractal dimensions of these generalized Cantor sets. Further, we have shown its application in detecting chaotic nature of the dynamics produced by iteration of piecewise linear maps.
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References
Falconer K (2003) Fractal geometry: mathematical foundation and applications, 2nd edn. Willey, Hoboken
Quevedo R, Carlos LG, Aguilera JM, Cadoche L (2002) Description of food surfaces and microstructural changes using fractal image texture analysis. J Food Eng 53(4):361–371
Peleg S, Naor J, Hartlui R, Avnir D (1984) Multiple resolution texture analysis and classification. IEEE Trans Pattern Anal Mach Intell PAMI 6(4):518–523
Isabelle T, Pierre F, Christophe B (2008) The morphology of built-up landscapes in Wallonia (Belgium): A classification using fractal indices. Landscape Urban Planing 84(2):99–115
Crilly AJ, Earnshaw R, Jones H et al (2013) Application of Fractals and Chaos: the shape of things. Springer, New York
Liu Y, Chen Y, Wang H, Jiang L, Zhang Y, Zhao J, Wang D, Zhao Y, Song Y (2014) An improved differential box-counting method to estimate fractal dimensions of gray-level images. J Vis Commun Image Represent 25(5):1102–1111
Liu Y, Chen L, Wang H, Jaing L, Zhao J, Wang D, Zhao Y (2014) An improved differential box counting method to estimate fractal dimensions of gray-level images. J Visual Commun Image Represent 25:1102–1111
Souza NTCM, Anselmo DHAL, Mello VD, Silva R (2014) Analysis of fractal groups of the type d-(m,r)-Cantord-(m,r)-Cantor within the framework of Kaniadakis Statistics. Phys Lett A 378(24):1691–1694
Keller JM, Chen S, Crownover RM (1989) Texture description and segmentation through fractal geometry. Comput Vis Graphics Image Process 45(2):150–166
Chaudhuri BB, Sarkar N (1995) Texture segmentation using fractal dimension. IEEE Trans Pattern Anal Mach Intell 17(1):72–77
Bruno et al (2008) Fractal dimension applied to plant identification. Inf Sci 178(12):2722–2733
Chakrabarti BK, Chatterjee A, Bhattacharyya P (2008) “Two-fractal overlap time series: Earthquakes and market crashes. PARAMA 71(2):203–210
Smalley RF Jr, Chatelain JL, Turcotte DL, Prevot R (1987) A fractal approach to the clustering of Earthquakes: application to the Seismicity of the New Hebrides. Bull Seismol Soc Am 77(3):1368–1381
Sezer A (2012) Employing Cantor sets for earthquakes time series analysis in two zones of western Turkey. Sci Iran A 19(6):1456–1462
Li J, Du Q, Sun C (2009) An improved box-counting method for image fractal dimension estimation. Pattern Recogn 42:2460–2469
Sarkar N, Chaudhuri BB (1994) An efficient differential box-counting approach to compute. Fractal Dimens Image IEEE 24(1):115–120
Devaney RL (1992) A First Course in Chaotic Dynamical Systems. Addition Wesley Publishing Company INC, New York
Hutchinsion JE (1981) Fractals and Self-similarity. Indiana University Mathematics Journal 30:713–747
Schoenfeld AH, Gruenhage G (1975) An alternative characterization of the Cantor set. Proc Am Math Soc 53(1):235–236
Maendes P (1999) Sum of Cantor sets: self-similarity and measure. Proc Am Math Soc 127:3305–3308
Peitgen HO, Jurgens H, Saupe D (2004) Chaos and fractals: new frontiers of science, 2nd edn. Springer, New York
Horiguchi T, Morita T (1984) Devil’s staircase in one dimensional mapping. Phys A 126(3):328–348
Horiguchi T, Morita T (1984) Fractal dimension related to Devil’s staircase for a family of piecewise linear mapping. Phys A 128(1–3):289–295
Dovgoshey O, Martio O, Ryazanov V, Vaorinen M (2006) The Cantor function. Expos Math 24(1):1–37
Lapidus ML, Lu H (2008) Non-archimedean cantor set and string. J fixed point theory appl 3(1):181–190
Shaver C (2009) An Exploration of the Cantor set. MT4960: Mathematics Seminar-Spring 2009, Rockhurst University’09, pp 1–19
Baek IS (2012) The parameter distributed set for a self-similar measure. Bull Korean Math Soc 49(5):1041–1055
Beak IS (2004) Cantor dimension and its applications. B Korean Math Soc 41(1):13–18
Beak IS (2003) Hausdorff dimension of perturbed cantor sets without some boundedness condition. Acta Math Hungar 99(4):279–283
Kumar A, Rani M, Chugh R (2013) New 5-adic cantor sets and fractal string. Springer Plus 2:654
Spyrou P (2013) The alternation of representation in case of Cantor set. Department of Mathematics, University of Athens, Athens
Goodson Geoffrey R (2015) Chaotic dynamics: fractals, tilings and substitution. Towson University, Towson
Lipschutz S (1965) General topology. Schaum’s outline series. Mc Grow Hill, New York
Grassberger P (1981) On the Hausdorff dimension of fractal attractors. J Stat Phys 26(1):173–179
Chatterjee S, Yilmaz MR (1992) Chaos, fractals and statistics. Stat Sci 7(1):49–121
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The authors are thankful to both the reviewers for their valuable comments, which help us to bring the paper in its present form.
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Appendix
Appendix
1.1 Proof of Theorem 2.1
Let \( \lambda \,\,{\text{and}}\,\,\varLambda \), respectively, be the lub (least upper bound) and glb (greatest lower bound) of the subset S of R. Consider the complement \( S^{c} = \left[ {\lambda ,\varLambda } \right] - S \) of S. Clearly, \( S^{c} \) is union of countably many open intervals. Let G be the collection of all such open intervals. Also, \( C^{c} = \left[ {0,\,\,1} \right] - C \) is a countable collection of open intervals. We denote this collection of open intervals by H. Now define \( \phi : \) G \( \to \) H as follows:
Let \( F_{1} \in \) G be the interval of maximal length. Then, \( \phi \left( {F_{1} } \right) = \left( {\frac{1}{3},\frac{2}{3}} \right) \in C^{c} \). Next, let \( F_{21} \) and \( F_{22} \) be the open intervals in G such that \( F_{21} \) is left and \( F_{22} \) is right to \( F_{1} \) and of maximal length among the members of G other than \( F_{1} \), then
In this way one, can define \( \phi \) on the whole set G, as G contains only finitely many sets of length greater than some fixed \( \varepsilon > 0 \) and since any two intervals in G or in H have different end points. Construction of \( \phi \) ensures that \( \phi \) is bijective and order preserving in the sense that if \( F_{\alpha } \) is to the left of \( F_{\beta } \), then \( \phi \left( {F_{\alpha } } \right) \) is to the left of \( \phi \left( {F_{\beta } } \right) \).
Now let us define \( f:\left[ {\lambda ,\varLambda } \right] \to \left[ {0,1} \right] \) as follows:
For \( F \in \) G, let \( \left. f \right|_{F} :F \to \phi \left( F \right) \) be the unique linear increasing map, which maps \( F \) bijectively to \( \phi \left( F \right) \). Since S and C are totally disconnected, they are nowhere dense, and thus, there is a continuation \( \xi :\left[ {\lambda ,\varLambda } \right] \to \left[ {0,1} \right] \) given by:
Let \( \psi = \left. \xi \right|_{S} \), then \( \psi :S \to C \) is monotone increasing, continuous bijective map. Now, we want to show that \( \zeta = \psi^{ - 1} \) is continuous. Clearly \( \zeta \) is again monotone increasing. Let \( x \in C\,\,{\text{and}}\;\,x_{n} \to x \). We need to show that \( \zeta \left( {x_{n} } \right) \to \zeta \left( x \right) \). Since the sequence \( \left\langle {x_{n} } \right\rangle \) contains a monotone subsequence, without loss of generality assume that \( \left\langle {x_{n} } \right\rangle \) itself is monotone increasing.
Now, \( y = \mathop {\lim }\limits_{n \to \infty } \zeta \left( {x_{n} } \right) = \mathop {\sup }\limits_{n \ge 1} \zeta \left( {x_{n} } \right) \le \zeta \left( x \right) \)
If possible, suppose \( y < \zeta \left( x \right) \). Since S is closed, we have \( y \in S \) and \( \zeta^{ - 1} \left( y \right) < x. \) This implies that \( y < x_{n} \) for large n. Therefore, by monotonicity \( y < \zeta \left( {x_{n} } \right) \) which contradicts the fact \( y = \mathop {\lim }\limits_{n \to \infty } \zeta \left( {x_{n} } \right) \). Thus, we must have \( y = \zeta \left( x \right)\,\,\,{\text{i}} . {\text{e}},\,\,\,\zeta \left( {x_{n} } \right) \to \zeta \left( x \right) \).□
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Choudhury, G., Mahanta, A., Sarmah, H.K. et al. Cantor Set as a Fractal and Its Application in Detecting Chaotic Nature of Piecewise Linear Maps. Proc. Natl. Acad. Sci., India, Sect. A Phys. Sci. 90, 749–759 (2020). https://doi.org/10.1007/s40010-019-00613-8
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DOI: https://doi.org/10.1007/s40010-019-00613-8