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Alpha-Stable Autoregressive Modeling of Chua's Circuit in the Presence of Heavy-Tailed Noise

Year 2023, Volume: 5 Issue: 1, 3 - 10, 31.03.2023
https://doi.org/10.51537/chaos.1162383

Abstract

This study presents alpha-stable autoregressive (AR) modeling of the dynamics of Chua's circuit in the presence of heavy-tailed noise. The parameters of the AR time series are estimated using the covariation-based Yule-Walker method, and the parameters of alpha-stable distributed residuals are calculated using the regression type method. Visual depictions of the calculated parameters of the AR model and alpha-stable distributions of residuals are presented. The medians of the estimated parameters of the AR model and alpha-stable distributions parameters of residuals are presented for heavy-tailed noise with various stability index parameters. Thus, the impulsive behavior of Chua's circuit can be modeled as alpha-stable AR time series, and the model can provide an alternative approach to describe the chaotic systems driven by heavy-tailed noise.

References

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  • Brockwell, P. J. and R. A. Davis, 2002 Introduction to time series and forecasting. Springer.
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  • Ditlevsen, P. D., 1999 Observation of α-stable noise induced millennial climate changes from an ice-core record. Geophysical Research Letters 26: 1441–1444.
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  • Gan, R., B. I. Ahmad, and S. J. Godsill, 2021 Lévy state-space models for tracking and intent prediction of highly maneuverable objects. IEEE Transactions on Aerospace and Electronic Systems 57.
  • Gan, R. and S. Godsill, 2020 α-stable lévy state-space models for manoeuvring object tracking. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp. 1–7, IEEE.
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  • Janicki, A. and A. Weron, 1993 Simulation and chaotic behavior of alpha-stable stochastic processes. CRC Press.
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  • Maleki, M., D.Wraith, M. R. Mahmoudi, and J. E. Contreras-Reyes, 2020 Asymmetric heavy-tailed vector auto-regressive processes with application to financial data. Journal of Statistical Computation and Simulation 90: 324–340.
  • McCulloch, J. H., 1996 13 financial applications of stable distributions. Handbook of statistics 14: 393–425.
  • Nikias, C. L. and M. Shao, 1995 Signal processing with alpha-stable distributions and applications. Wiley-Interscience.
  • Nolan, J., 2003 Stable distributions: models for heavy-tailed data. Birkhauser New York.
  • Pai, J. S. and N. Ravishanker, 2010 Fast bayesian estimation for varfima processes with stable errors. Journal of Statistical Theory and Practice 4: 663–677.
  • Platen, E., 1999 An introduction to numerical methods for stochastic differential equations. Acta numerica 8: 197–246.
  • Samorodnitsky, G. and M. S. Taqqu, 1994 Stable Non-Gaussian Random Processes. Chapman & Hall.
  • Savaci, F. A. and S. Yilmaz, 2015 Bayesian stable mixture model of state densities of generalized chua’s circuit. International Journal of Bifurcation and Chaos 25: 1550038.
  • Schäfer, B., C. Beck, K. Aihara, D.Witthaut, and M. Timme, 2018 Non-gaussian power grid frequency fluctuations characterized by lévy-stable laws and superstatistics. Nature Energy 3: 119– 126.
  • Suykens, J. A. and A. Huang, 1997 A family of n-scroll attractors from a generalized chua’s circuit. Archiv fur Elektronik und Ubertragungstechnik 51: 131–137.
  • Van den Heuvel, F., B. George, N. Schreuder, and F. Fiorini, 2018 Using stable distributions to characterize proton pencil beams. Medical physics 45: 2278–2288.
  • Van den Heuvel, F., S. Hackett, F. Fiorini, C. Taylor, S. Darby, et al., 2015 Su-f-brd-04: Robustness analysis of proton breast treatments using an alpha-stable distribution parameterization. Medical Physics 42: 3526–3526.
  • Wesselhöfft, N., 2021 Utilizing self-similar stochastic processes to model rare events in finance .
  • Wolf, A., J. B. Swift, H. L. Swinney, and J. A. Vastano, 1985 Determining lyapunov exponents from a time series. Physica D: nonlinear phenomena 16: 285–317.
  • Yilmaz, S., M. E. Cek, and F. A. Savaci, 2018 Stochastic bifurcation in generalized chua’s circuit driven by skew-normal distributed noise. Fluctuation and Noise Letters 17: 1830002.
Year 2023, Volume: 5 Issue: 1, 3 - 10, 31.03.2023
https://doi.org/10.51537/chaos.1162383

Abstract

References

  • Anvari, M., L. R. Gorjão, M. Timme, D.Witthaut, B. Schäfer, et al., 2020 Stochastic properties of the frequency dynamics in real and synthetic power grids. Physical review research 2: 013339.
  • Argyris, J., I. Andreadis, G. Pavlos, and M. Athanasiou, 1998 The influence of noise on the correlation dimension of chaotic attractors. Chaos, Solitons & Fractals 9: 343–361.
  • Brockwell, P. J. and R. A. Davis, 2002 Introduction to time series and forecasting. Springer.
  • Broszkiewicz-Suwaj, E. and A.Wyłoma´ nska, 2021 Application of non-gaussian multidimensional autoregressive model for climate data prediction. International Journal of Advances in Engineering Sciences and Applied Mathematics 13: 236–247.
  • Clavier, L., T. Pedersen, I. R. Larrad, and M. Egan, 2021 Alphastable model for interference in iot networks. In 2021 IEEE Conference on Antenna Measurements & Applications (CAMA), pp. 575– 578, IEEE.
  • Contreras-Reyes, J. E., 2021 Chaotic systems with asymmetric heavy-tailed noise: Application to 3d attractors. Chaos, Solitons & Fractals 145: 110820.
  • Contreras-Reyes, J. E., 2022 Rényi entropy and divergence for varfima processes based on characteristic and impulse response functions. Chaos, Solitons & Fractals 160: 112268.
  • Ditlevsen, P. D., 1999 Observation of α-stable noise induced millennial climate changes from an ice-core record. Geophysical Research Letters 26: 1441–1444.
  • Gallagher, C. M., 2001 A method for fitting stable autoregressive models using the autocovariation function. Statistics & probability letters 53: 381–390.
  • Gan, R., B. I. Ahmad, and S. J. Godsill, 2021 Lévy state-space models for tracking and intent prediction of highly maneuverable objects. IEEE Transactions on Aerospace and Electronic Systems 57.
  • Gan, R. and S. Godsill, 2020 α-stable lévy state-space models for manoeuvring object tracking. In 2020 IEEE 23rd International Conference on Information Fusion (FUSION), pp. 1–7, IEEE.
  • Grzesiek, A., M. Mrozi ´ nska, P. Giri, S. Sundar, and A.Wyłoma´ nska, 2021 The covariation-based yule–walker method for multidimensional autoregressive time series with α-stable distributed noise. International Journal of Advances in Engineering Sciences and Applied Mathematics 13: 394–414.
  • Janczura, J., S. Orzeł, and A. Wyłoma´ nska, 2011 Subordinated α- stable ornstein–uhlenbeck process as a tool for financial data description. Physica A: Statistical Mechanics and its Applications 390: 4379–4387.
  • Janicki, A. and A. Weron, 1993 Simulation and chaotic behavior of alpha-stable stochastic processes. CRC Press.
  • Kruczek, P., A. Wyłoma´ nska, M. Teuerle, and J. Gajda, 2017 The modified yule-walker method for α-stable time series models. Physica A: Statistical Mechanics and its Applications 469: 588– 603.
  • Maleki, M., D.Wraith, M. R. Mahmoudi, and J. E. Contreras-Reyes, 2020 Asymmetric heavy-tailed vector auto-regressive processes with application to financial data. Journal of Statistical Computation and Simulation 90: 324–340.
  • McCulloch, J. H., 1996 13 financial applications of stable distributions. Handbook of statistics 14: 393–425.
  • Nikias, C. L. and M. Shao, 1995 Signal processing with alpha-stable distributions and applications. Wiley-Interscience.
  • Nolan, J., 2003 Stable distributions: models for heavy-tailed data. Birkhauser New York.
  • Pai, J. S. and N. Ravishanker, 2010 Fast bayesian estimation for varfima processes with stable errors. Journal of Statistical Theory and Practice 4: 663–677.
  • Platen, E., 1999 An introduction to numerical methods for stochastic differential equations. Acta numerica 8: 197–246.
  • Samorodnitsky, G. and M. S. Taqqu, 1994 Stable Non-Gaussian Random Processes. Chapman & Hall.
  • Savaci, F. A. and S. Yilmaz, 2015 Bayesian stable mixture model of state densities of generalized chua’s circuit. International Journal of Bifurcation and Chaos 25: 1550038.
  • Schäfer, B., C. Beck, K. Aihara, D.Witthaut, and M. Timme, 2018 Non-gaussian power grid frequency fluctuations characterized by lévy-stable laws and superstatistics. Nature Energy 3: 119– 126.
  • Suykens, J. A. and A. Huang, 1997 A family of n-scroll attractors from a generalized chua’s circuit. Archiv fur Elektronik und Ubertragungstechnik 51: 131–137.
  • Van den Heuvel, F., B. George, N. Schreuder, and F. Fiorini, 2018 Using stable distributions to characterize proton pencil beams. Medical physics 45: 2278–2288.
  • Van den Heuvel, F., S. Hackett, F. Fiorini, C. Taylor, S. Darby, et al., 2015 Su-f-brd-04: Robustness analysis of proton breast treatments using an alpha-stable distribution parameterization. Medical Physics 42: 3526–3526.
  • Wesselhöfft, N., 2021 Utilizing self-similar stochastic processes to model rare events in finance .
  • Wolf, A., J. B. Swift, H. L. Swinney, and J. A. Vastano, 1985 Determining lyapunov exponents from a time series. Physica D: nonlinear phenomena 16: 285–317.
  • Yilmaz, S., M. E. Cek, and F. A. Savaci, 2018 Stochastic bifurcation in generalized chua’s circuit driven by skew-normal distributed noise. Fluctuation and Noise Letters 17: 1830002.
There are 30 citations in total.

Details

Primary Language English
Subjects Electrical Engineering
Journal Section Research Articles
Authors

Serpil Yılmaz 0000-0002-6276-6058

Deniz Kutluay 0000-0001-5182-2870

Publication Date March 31, 2023
Published in Issue Year 2023 Volume: 5 Issue: 1

Cite

APA Yılmaz, S., & Kutluay, D. (2023). Alpha-Stable Autoregressive Modeling of Chua’s Circuit in the Presence of Heavy-Tailed Noise. Chaos Theory and Applications, 5(1), 3-10. https://doi.org/10.51537/chaos.1162383

Chaos Theory and Applications in Applied Sciences and Engineering: An interdisciplinary journal of nonlinear science 23830 28903   

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