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Year 2019, , 130 - 138, 20.12.2019
https://doi.org/10.33401/fujma.587245

Abstract

References

  • [1] A. Boyarsky,A matrix method for estimationg the Liapunov exponent of one-dimensional systems, Journal of Statistical Physics, Vol. 50, No. 1 – 2, 1988.
  • [2] J. M. Borwein and A. S. Lewis, Convergence of the best entropy estimates, SIAM J. Optim. 1(2), 191 – 205.
  • [3] P. Biswas, H. Shimoyama and R. L. Mead, Lyapunov exponents and the natural invariant density determination of chaotic maps: an iterative maximumentropy ansatz, Journal of Physics A, Vol. 43, 2010
  • [4] C. J. Bose and R. Murray, Dynamical conditions for convergence of a maximum entropy method for Frobenius-Perron operator equations., Appl. Math.Comput. 182, N0. 1, 2006.
  • [5] P. Bryant, R. Brown and H. D. I. Abarbenel, Lyapunov Exponents from observed Time series, Physics Review letters, Vol. 65, No. 13, 1523 – 1526, 1990.
  • [6] J. Ding and N. H. Rhee, A unified maximum entropy method via spline functions for Frobenius -Perron operators, Numer. Algebra Control Optim. 3, no.2, 235 – 245, 2013.
  • [7] J. Ding, A maximum entropy method for solving Frobenius-Perron equations , Appl. Math. Comp., 93, 155 –168, 1998.
  • [8] J. Ding, C. Jin, N. H. Rhee and A. Zhou, A maximum entropy method based on piecewise linear functions for the recovery of a stationary density ofinterval maps, J. Stat Phys 145, 2011, 1620–1639, 2011.
  • [9] J. Ding and R. L. Mead, The maximum entropy method applied to stationary density computation, Appl. Math. Comp. 185, 658 – 666, 2007.
  • [10] J. Ding and N. H. Rhee, A maximum entropy method based on orthogonal polynomials for Frobenius-Perron operators , Adv. Applied Math. Mec., 3 ,2011.
  • [11] J. Ding and N. H. Rhee, Birkhoff’s ergodic theorem and the piecewise constant maximum entropy method for Frobenius-Perron operators , Inter. J.Computer Math., 89, 2012.
  • [12] S. Ellner, A. R. Gallant, D. McCaffrey and D. Nychka, Convergence rates and data requirements for Jacobian-based estimates of Lyapunov exponentsfrom data, Physics Letters A, Volume 153, Issues 6–7, 1991, Pages 357 – 363.
  • [13] G. Froyland, K. Judd and A. I. Mess, Estimation of dynamical systems using a spatial average, Phys. Rev. E (3) 51, no. 4, part A, 2844 – 2855, 1995.
  • [14] G. Gencaya and W. D. Dechert, An algorithm for the n Lyapunov exponents of an n-dimensional unknown dynamical system, Physica D: NonlinearPhenomena, Volume 59, Issues 1 – 3, Pages 142 – 157, 1992.
  • [15] M. S. Islam, Maximum entropy method for position dependent random maps, Internat. J. Bifur. Chaos Appl. Sci. Engrg, Vol. 21, No. 6, 1805 – 1811,2011.
  • [16] M. S. Islam, A piecewise quadratic maximum entropy method for invariant measures of position dependent random maps, Dyn. Contin. Discrete Impuls.Syst. Ser. A Math. Anal. 24, no. 6, 431 – 445, 2017;
  • [17] E. T. Jaynes, Information theory and statistical mechanics , Phys. Rev. 106, 620 – 630, 1957.
  • [18] A. Lasota and M. C. Mackey, Chaos, fractals, and noise. Stochastic aspects of dynamics, Applied Mathematical Sciences 97, Springer-Verlag, NewYork, 1994.
  • [19] A. Lasota and J. A. Yorke, On the existence of invariant measures forpiecewise monotonic transformations, Trans. Amer. Math. Soc. 186 ,481 – 488,1973.
  • [20] A. M. Lyapunov, Probl`eme G´en´eral de la Stabilit´e du Mouvement (French), Annals of Mathematics Studies, no. 17. Princeton University Press,Princeton, N. J.; Oxford University Press, London, 1947. iv+272 pp.
  • [21] L. R. Mead and N. Papanicolaou, Maximum entropy in the problem of moments,J. Math. Phys. 25, 2404 - -2417, 1984.
  • [22] V. I. Oseledec, A multiplicative ergodic theorem. Characteristic Ljapunov, exponents of dynamical systems (Russian), Trudy Moskov. Mat. Obˇsˇc. 19, 79– 210, 1968.
  • [23] C. Robinson, Dynamical systems : stability, symbolic dynamics, and chaos, Boca Raton : CRC Press, 1995.
  • [24] T. Upadhay, J. Ding and N. H. Rhee, A piecewise quadratic maximum entropy method for the statistical study of chaos, J. Math. Anal. Appl. 421,1487–1501, 2015.
  • [25] A. Wolf Quantifying chaos with Lyapunov exponents, Chaos, 273–290, Nonlinear Sci. Theory Appl., Manchester Univ. Press, Manchester, 1986;

Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method

Year 2019, , 130 - 138, 20.12.2019
https://doi.org/10.33401/fujma.587245

Abstract

In this paper, we study the computation of Lyapunov exponents  for deterministic dynamical systems  via a general piecewise spline maximum entropy method. We present a comparison of computations of Lyapunov exponents between a piecewise linear,  a piecewise quadratic and a piecewise cubic maximum entropy methods. In order to compute  Lyapunov exponents for deterministic maps,  we also compute density functions of their invariant measures via piecewise spline maximum entropy method.

References

  • [1] A. Boyarsky,A matrix method for estimationg the Liapunov exponent of one-dimensional systems, Journal of Statistical Physics, Vol. 50, No. 1 – 2, 1988.
  • [2] J. M. Borwein and A. S. Lewis, Convergence of the best entropy estimates, SIAM J. Optim. 1(2), 191 – 205.
  • [3] P. Biswas, H. Shimoyama and R. L. Mead, Lyapunov exponents and the natural invariant density determination of chaotic maps: an iterative maximumentropy ansatz, Journal of Physics A, Vol. 43, 2010
  • [4] C. J. Bose and R. Murray, Dynamical conditions for convergence of a maximum entropy method for Frobenius-Perron operator equations., Appl. Math.Comput. 182, N0. 1, 2006.
  • [5] P. Bryant, R. Brown and H. D. I. Abarbenel, Lyapunov Exponents from observed Time series, Physics Review letters, Vol. 65, No. 13, 1523 – 1526, 1990.
  • [6] J. Ding and N. H. Rhee, A unified maximum entropy method via spline functions for Frobenius -Perron operators, Numer. Algebra Control Optim. 3, no.2, 235 – 245, 2013.
  • [7] J. Ding, A maximum entropy method for solving Frobenius-Perron equations , Appl. Math. Comp., 93, 155 –168, 1998.
  • [8] J. Ding, C. Jin, N. H. Rhee and A. Zhou, A maximum entropy method based on piecewise linear functions for the recovery of a stationary density ofinterval maps, J. Stat Phys 145, 2011, 1620–1639, 2011.
  • [9] J. Ding and R. L. Mead, The maximum entropy method applied to stationary density computation, Appl. Math. Comp. 185, 658 – 666, 2007.
  • [10] J. Ding and N. H. Rhee, A maximum entropy method based on orthogonal polynomials for Frobenius-Perron operators , Adv. Applied Math. Mec., 3 ,2011.
  • [11] J. Ding and N. H. Rhee, Birkhoff’s ergodic theorem and the piecewise constant maximum entropy method for Frobenius-Perron operators , Inter. J.Computer Math., 89, 2012.
  • [12] S. Ellner, A. R. Gallant, D. McCaffrey and D. Nychka, Convergence rates and data requirements for Jacobian-based estimates of Lyapunov exponentsfrom data, Physics Letters A, Volume 153, Issues 6–7, 1991, Pages 357 – 363.
  • [13] G. Froyland, K. Judd and A. I. Mess, Estimation of dynamical systems using a spatial average, Phys. Rev. E (3) 51, no. 4, part A, 2844 – 2855, 1995.
  • [14] G. Gencaya and W. D. Dechert, An algorithm for the n Lyapunov exponents of an n-dimensional unknown dynamical system, Physica D: NonlinearPhenomena, Volume 59, Issues 1 – 3, Pages 142 – 157, 1992.
  • [15] M. S. Islam, Maximum entropy method for position dependent random maps, Internat. J. Bifur. Chaos Appl. Sci. Engrg, Vol. 21, No. 6, 1805 – 1811,2011.
  • [16] M. S. Islam, A piecewise quadratic maximum entropy method for invariant measures of position dependent random maps, Dyn. Contin. Discrete Impuls.Syst. Ser. A Math. Anal. 24, no. 6, 431 – 445, 2017;
  • [17] E. T. Jaynes, Information theory and statistical mechanics , Phys. Rev. 106, 620 – 630, 1957.
  • [18] A. Lasota and M. C. Mackey, Chaos, fractals, and noise. Stochastic aspects of dynamics, Applied Mathematical Sciences 97, Springer-Verlag, NewYork, 1994.
  • [19] A. Lasota and J. A. Yorke, On the existence of invariant measures forpiecewise monotonic transformations, Trans. Amer. Math. Soc. 186 ,481 – 488,1973.
  • [20] A. M. Lyapunov, Probl`eme G´en´eral de la Stabilit´e du Mouvement (French), Annals of Mathematics Studies, no. 17. Princeton University Press,Princeton, N. J.; Oxford University Press, London, 1947. iv+272 pp.
  • [21] L. R. Mead and N. Papanicolaou, Maximum entropy in the problem of moments,J. Math. Phys. 25, 2404 - -2417, 1984.
  • [22] V. I. Oseledec, A multiplicative ergodic theorem. Characteristic Ljapunov, exponents of dynamical systems (Russian), Trudy Moskov. Mat. Obˇsˇc. 19, 79– 210, 1968.
  • [23] C. Robinson, Dynamical systems : stability, symbolic dynamics, and chaos, Boca Raton : CRC Press, 1995.
  • [24] T. Upadhay, J. Ding and N. H. Rhee, A piecewise quadratic maximum entropy method for the statistical study of chaos, J. Math. Anal. Appl. 421,1487–1501, 2015.
  • [25] A. Wolf Quantifying chaos with Lyapunov exponents, Chaos, 273–290, Nonlinear Sci. Theory Appl., Manchester Univ. Press, Manchester, 1986;
There are 25 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Articles
Authors

Md Shafiqul Islam 0000-0002-5389-2634

Publication Date December 20, 2019
Submission Date July 4, 2019
Acceptance Date November 16, 2019
Published in Issue Year 2019

Cite

APA Islam, M. S. (2019). Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method. Fundamental Journal of Mathematics and Applications, 2(2), 130-138. https://doi.org/10.33401/fujma.587245
AMA Islam MS. Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method. Fundam. J. Math. Appl. December 2019;2(2):130-138. doi:10.33401/fujma.587245
Chicago Islam, Md Shafiqul. “Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method”. Fundamental Journal of Mathematics and Applications 2, no. 2 (December 2019): 130-38. https://doi.org/10.33401/fujma.587245.
EndNote Islam MS (December 1, 2019) Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method. Fundamental Journal of Mathematics and Applications 2 2 130–138.
IEEE M. S. Islam, “Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method”, Fundam. J. Math. Appl., vol. 2, no. 2, pp. 130–138, 2019, doi: 10.33401/fujma.587245.
ISNAD Islam, Md Shafiqul. “Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method”. Fundamental Journal of Mathematics and Applications 2/2 (December 2019), 130-138. https://doi.org/10.33401/fujma.587245.
JAMA Islam MS. Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method. Fundam. J. Math. Appl. 2019;2:130–138.
MLA Islam, Md Shafiqul. “Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method”. Fundamental Journal of Mathematics and Applications, vol. 2, no. 2, 2019, pp. 130-8, doi:10.33401/fujma.587245.
Vancouver Islam MS. Lyapunov Exponents of One Dimensional Chaotic Dynamical Systems via a General Piecewise Spline Maximum Entropy Method. Fundam. J. Math. Appl. 2019;2(2):130-8.

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