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A new numerical algorithm for fractional Fitzhugh–Nagumo equation arising in transmission of nerve impulses

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Abstract

The principal objective of this study is to present a new numerical scheme based on a combination of q-homotopy analysis approach and Laplace transform approach to examine the Fitzhugh–Nagumo (F–N) equation of fractional order. The F–N equation describes the transmission of nerve impulses. In order to handle the nonlinear terms, the homotopy polynomials are employed. To validate the results derived by employing the used scheme, we study the F–N equation of arbitrary order by using the fractional reduced differential transform scheme. The error analysis of the proposed approach is also discussed. The outcomes are shown through the graphs and tables that elucidate that the used schemes are very fantastic and accurate.

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References

  1. Fitzhugh, R.: Impulse and physiological states in models of nerve membrane. Biophys. J. 1, 445–466 (1961)

    Article  Google Scholar 

  2. Nagumo, J.S., Arimoto, S., Yoshizawa, S.: An active pulse transmission line simulating nerve axon. Proc. IRE 50, 2061–2070 (1962)

    Article  Google Scholar 

  3. Jone, D.S., Sleeman, B.D.: Differential Equations and Mathematical Biology. Chapman Hall/CRC, New York (2003)

    Google Scholar 

  4. Shih, M., Momoniat, E., Mahomed, F.M.: Approximate conditional symmetries and approximate solutions of the perturbed Fitzhugh–Nagumo equation. J. Math. Phys. 46, 023503 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  5. Kawahara, T., Tanaka, M.: Interaction of travelling fronts: an exact solution of a nonlinear diffusion equation. Phys. Lett. A 97, 311–314 (1983)

    Article  MathSciNet  Google Scholar 

  6. Nucci, M.C., Clarkson, P.A.: The nonclassical method is more general than the direct method for symmetry reductions: an example of the Fitzhugh–Nagumo equation. Phys. Lett. A 164, 49–56 (1992)

    Article  MathSciNet  Google Scholar 

  7. Li, H., Guo, Y.: New exact solutions to the Fitzhugh–Nagumo equation. Appl. Math. Comput. 180, 524–528 (2006)

    MathSciNet  MATH  Google Scholar 

  8. Abbasbandy, S.: Soliton solutions for the Fitzhugh–Nagumo equation with the homotopy analysis method. Appl. Math. Model. 32, 2706–2714 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  9. Kakiuchi, N., Tchizawa, K.: On an explicit duck solution and delay in the Fitzhugh–Nagumo equation. J. Differ. Equ. 141, 327–339 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  10. Schonbek, M.E.: Boundary value problems for the Fitzhugh–Nagumo equations. J. Differ. Equ. 30, 119–147 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  11. Yanagida, E.: Stability of travelling front solutions of the Fitzhugh–Nagumo equations. Math. Comput. Model. 12, 289–301 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  12. Jackson, D.E.: Error estimates for the semidiscrete Galerkin approximations of the Fitzhugh–Nagumo equations. Appl. Math. Comput. 50, 93–114 (1992)

    MathSciNet  MATH  Google Scholar 

  13. Gao, W., Wang, J.: Existence of wavefronts and impulses to Fitzhugh–Nagumo equations. Nonlinear Anal. 57, 5–6 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  14. Olmos, D., Shizgal, B.D.: Pseudospectral method of solution of the Fitzhugh–Nagumo equation. Math. Comput. Simul. 79, 2258–2278 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  15. Dehghan, M., Heris, J.M., Saadatmandi, A.: Application of semi-analytic methods for the Fitzhugh–Nagumo equation, which models the transmission of nerve impulses. Math. Methods Appl. Sci. (2010). doi:10.1002/mma.1329

  16. Miller, K.S., Ross, B.: An Introduction to the Fractional Calculus and Fractional Differential Equations. Willey, New York (1993)

    MATH  Google Scholar 

  17. Podlubny, I.: Fractional Differential Equations, vol. 198, p. 340. Academic Press, San Diego (1999)

    MATH  Google Scholar 

  18. Caputo, M.: Elasticita e Dissipazione. Zani-Chelli, Bologna (1969)

    Google Scholar 

  19. Kilbas, A.A., Srivastava, H.M.: Theory and Applications of Fractional Differential Equations, vol. 204, p. 540. Elsevier, Amsterdam (2006)

    Book  Google Scholar 

  20. Baskonus, H.M., Mekkaoui, T., Hammouch, Z., Bulut, H.: Active control of a chaotic fractional order economic system. Entropy 17(8), 5771–5783 (2015)

    Article  Google Scholar 

  21. Singh, J., Kumar, D., Nieto, J.J.: A reliable algorithm for local fractional Tricomi equation arising in fractal transonic flow. Entropy 18(6), 206 (2016)

    Article  MathSciNet  Google Scholar 

  22. Hristov, J.: Transient heat diffusion with a non-singular fading memory: from the Cattaneo constitutive equation with Jeffrey’s kernel to the Caputo–Fabrizio time-fractional derivative. Therm. Sci. 20(2), 765–770 (2016)

    Article  Google Scholar 

  23. Kumar, D., Singh, J., Baleanu, D.: A hybrid computational approach for Klein–Gordon equations on Cantor sets. Nonlinear Dyn. 87, 511–517 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  24. Kumar, D., Singh, J., Baleanu, D.: Modified Kawahara equation within a fractional derivative with non-singular kernel. Therm. Sci. (2017). doi:10.2298/TSCI160826008K

  25. Yang, X.J., Machado, J.A.T., Baleanu, D.: On exact traveling-wave solutions for local fractional Korteweg–de Vries equation. Chaos 26, 084312 (2016)

    Article  MathSciNet  Google Scholar 

  26. Area, I., Batarfi, H., Losada, J., Nieto, J.J., Shammakh, W., Torres, A.: On a fractional order Ebola epidemic model. Adv. Differ. Equ. (2015). doi:10.1186/s13662-015-0613-5

  27. Carvalho, A., Pinto, C.M.A.: A delay fractional order model for the co-infection of malaria and HIV/AIDS. Int. J. Dyn. Control 5, 168–186 (2017)

    Article  MathSciNet  Google Scholar 

  28. Machado, Z.A.T., Lopes, A.M.: Relative fractional dynamics of stock markets. Nonlinear Dyn. 86(3), 1613–1619 (2016)

    Article  MathSciNet  Google Scholar 

  29. Zhao, D., Singh, J., Kumar, D., Rathore, S., Yang, X.J.: An efficient computational technique for local fractional heat conduction equations in fractal media. J. Nonlinear Sci. Appl. 10, 1478–1486 (2017)

    Article  MathSciNet  Google Scholar 

  30. Ahmadian, A., Ismail, F., Salahshour, S., Baleanu, D., Ghaemi, F.: Uncertain viscoelastic models with fractional order: a new spectral tau method to study the numerical simulations of the solution. Commun. Nonlinear Sci. Numer. Simul. 53, 44–64 (2017)

    Article  MathSciNet  Google Scholar 

  31. Zaky, M.A., Machado, Z.A.T.: On the formulation and numerical simulation of distributed-order fractional optimal control problems. Commun. Nonlinear Sci. Numer. Simul. 52, 177–189 (2017)

    Article  MathSciNet  Google Scholar 

  32. Liao, S.J.: Beyond Perturbation: Introduction to Homotopy Analysis Method. Chapman and Hall/CRC Press, Boca Raton (2003)

    Book  Google Scholar 

  33. Liao, S.J.: On the homotopy analysis method for nonlinear problems. Appl. Math. Comput. 147, 499–513 (2004)

    MathSciNet  MATH  Google Scholar 

  34. Liao, S.J.: An approximate solution technique not depending on small parameters: a special example. Int. J. Non-linear Mech. 30(3), 371–380 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  35. El-Tawil, M.A., Huseen, S.N.: The \(q\)-homotopy analysis method (\(q\)-HAM). Int. J. Appl. Math. Mech. 8, 51–75 (2012)

    Google Scholar 

  36. El-Tawil, M.A., Huseen, S.N.: On convergence of the \(q\)-homotopy analysis method. Int. J. Contemp. Math. Sci. 8, 481–497 (2013)

    Article  MathSciNet  Google Scholar 

  37. Khuri, S.A.: A Laplace decomposition algorithm applied to a class of nonlinear differential equations. J. Appl. Math. 1, 141–155 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  38. Khan, M., Gondal, M.A., Hussain, I., Karimi Vanani, S.: A new comparative study between homotopy analysis transform method and homotopy perturbation transform method on semi-infinite domain. Math. Comput. Model. 55, 1143–1150 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  39. Singh, J., Swroop, R., Kumar, D.: A computational approach for fractional convection–diffusion equation via integral transforms. Ain Shams Eng. J. (2016). Doi:10.1016/j.asej.2016.04.014

  40. Kumar, D., Singh, J., Baleanu, D.: A fractional model of convective radial fins with temperature-dependent thermal conductivity. Rom. Rep. Phys. 69(1), 103 (2017)

    Google Scholar 

  41. Kumar, D., Agarwal, R.P., Singh, J.: A modified numerical scheme and convergence analysis for fractional model of Lienard’s equation. J. Comput. Appl. Math. (2017). Doi:10.1016/j.cam.2017.03.011

  42. Singh, J., Swroop, R., Kumar, D.: Numerical solution of time- and space-fractional coupled Burgers equations via homotopy algorithm. Alex. Eng. J. 55(2), 1753–1763 (2016)

    Article  Google Scholar 

  43. Srivastava, H.M., Kumar, D., Singh, J.: An efficient analytical technique for fractional model of vibration equation. Appl. Math. Model. 45, 192–204 (2017)

    Article  MathSciNet  Google Scholar 

  44. Odibat, Z., Bataineh, S.A.: An adaptation of homotopy analysis method for reliable treatment of strongly nonlinear problems: construction of homotopy polynomials. Math. Methods Appl. Sci. (2014). Doi:10.1002/mma.3136

  45. Keskin, Y., Oturanc, G.: Reduced differential transform method: a new approach to fractional partial differential equations. Nonlinear Sci. Lett. A 1, 61–72 (2010)

    MATH  Google Scholar 

  46. Gupta, P.K.: Approximate analytical solutions of fractional Benney–Lin equation by reduced differential transform method and the homotopy perturbation method. Comput. Math. Appl. 58, 2829–2842 (2011)

    Article  MathSciNet  MATH  Google Scholar 

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Acknowledgements

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the final version of the article.

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Correspondence to Devendra Kumar.

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Kumar, D., Singh, J. & Baleanu, D. A new numerical algorithm for fractional Fitzhugh–Nagumo equation arising in transmission of nerve impulses. Nonlinear Dyn 91, 307–317 (2018). https://doi.org/10.1007/s11071-017-3870-x

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  • DOI: https://doi.org/10.1007/s11071-017-3870-x

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