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Fractal Stationary Density in Coupled Maps

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Fractals in Engineering

Summary

We study the invariant measure or the stationary density of a coupled discrete dynamical system as a function of the coupling parameter ε (0 < ε < 1/4). The dynamical system considered is chaotic and unsynchronized for this range of parameter values. We find that the stationary density, restricted on the synchronization manifold, is a fractal function. We find the lower bound on the fractal dimension of the graph of this function and show that it changes continuously with the coupling parameter.

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References

  1. A. Pikovsky, M. Rosenblum, and J. Kurths. Synchronization-A Universal Concept in Nonlinear Science. Cambridge University Press, 2001.

    Google Scholar 

  2. L. M. Pecora, T. L. Carroll, G. A. Johnson, D. J. Mar, and J. F. Heagy. Fundamentals of synchronization in chaotic systems, concepts, and applications. Chaos, 7:520, 1997.

    Article  MathSciNet  Google Scholar 

  3. G. D. VanWiggeren and R. Roy. Communication with chaotic lasers. Science, 279:1198, 1998.

    Article  Google Scholar 

  4. D. Hansel and H. Sompolinsky. Synchronization and computation in a chaotic neural network. Phys. Rev. Lett., 68:718, 1992.

    Article  Google Scholar 

  5. G. Buzsáki and A. Draguhn. Neuronal oscillations in cortical networks. Science, 304:1926, 2004.

    Article  Google Scholar 

  6. R. W. Friedrich, C. J. Habermann, and G. Laurent. Multiplexing using synchrony in the zebrafish olfactory bulb. Nature Neuroscience, 7:862, 2004.

    Article  Google Scholar 

  7. J. Jost and K. M. Kolwankar. Global analysis of synchronization in coupled maps, 2004.

    Google Scholar 

  8. J. Jost and M. P. Joy. Spectral properties and synchronization in coupled map lattices. Phys. Rev. E, 65(1):016201, 2002.

    Article  MathSciNet  Google Scholar 

  9. A. Lasota and M. C. Mackey. Chaos, Fractals and Noise. Springer, 1994.

    Google Scholar 

  10. K. Falconer. Fractal Geometry-Mathematical Foundations and Applications. John Wiley, 1990.

    Google Scholar 

  11. P. L. Krapivsky and S. Redner. Random walk with shrinking steps. Am. J. Phys., 72:591, 2004.

    Article  Google Scholar 

  12. S. Jaffard. Multifractal formalism for functions part ii: Self-similar functions. SIAM J. Math. Anal., 28:971, 1997.

    Article  MATH  MathSciNet  Google Scholar 

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© 2005 Springer-Verlag London Limited

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Jost, J., Kolwankar, K.M. (2005). Fractal Stationary Density in Coupled Maps. In: Lévy-Véhel, J., Lutton, E. (eds) Fractals in Engineering. Springer, London. https://doi.org/10.1007/1-84628-048-6_4

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  • DOI: https://doi.org/10.1007/1-84628-048-6_4

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-047-4

  • Online ISBN: 978-1-84628-048-1

  • eBook Packages: EngineeringEngineering (R0)

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