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A novel operational matrix method based on Genocchi polynomials for solving n-dimensional stochastic Itô–Volterra integral equation

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Abstract

A reliable numerical method has been presented in this article to solve n-dimensional stochastic Itô–Volterra integral equations. In the proposed approach, relying on the valuable properties of Genocchi polynomials, operational matrices and related coefficient matrix have been introduced to convert the n-dimensional stochastic Itô–Volterra integral equation into a linear or nonlinear algebraic equation. Then collocation points have been used to generate the system of algebraic equations, which can be further solved by Newton’s method. Also, convergence analysis of the discussed technique is established. Finally, few illustrative problems have been examined to prove the efficiency and accuracy of the proposed scheme.

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References

  1. Nemati, S., Ordokhani, Y.: “Legendre expansion methods for the numerical solution of nonlinear 2D Fredholm integral equations of the second kind. J. Appl. Math. and Informatics 31, 609–621 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  2. Isah, A., Phang, C., Phang, P.: Collocation method based on Genocchi operational matrix for solving generalized fractional pantograph equations. Int. J. Differ. Equ. 2017, 10 (2017)

    MathSciNet  MATH  Google Scholar 

  3. Behera, S., Saha Ray, S.: Euler wavelets method for solving fractional-order linear Volterra–Fredholm integro-differential equations with weakly singular kernels. Comput. Appl. Math. 40(6), 30 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  4. Isah, A., Phang, C.: New operational matrix of derivative for solving non-linear fractional differential equations via Genocchi polynomials. J. King Saud Univ. Sci. 31(1), 1–7 (2019)

    Article  Google Scholar 

  5. Dehestani, H., Ordokhani, Y., Razzaghi, M.: The novel operational matrices based on 2D-Genocchi polynomials: solving a general class of variable-order fractional. Comput. Appl. Math. 39(4), 32 (2020)

    Article  MATH  Google Scholar 

  6. Sweilam, N.H., Nagy, A.M., Youssef, I.K., Mokhtar, M.M.: New spectral second kind Chebyshev wavelets scheme for solving systems of integro-differential equations. Int. J. Appl. Comput. Math 3(2), 333–345 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  7. Khajehnasiri, A.A.: Numerical solution of nonlinear 2D Volterra–Fredholm integro-differential equations by two-dimensional triangular function. Int. J. Appl. Comput. Math. 2(4), 575–591 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  8. He, J.H., Taha, M.H., Ramadan, M.A., Moatimid, G.M.: Improved block-pulse functions for numerical solution of mixed Volterra–Fredholm integral equations. Axioms 10(3), 200 (2021)

    Article  Google Scholar 

  9. He, J.H.: A simple approach to Volterra–Fredholm integral equations. J. Appl. Comput. Mech. 6(Special Issue), 1184–1186 (2020)

    Google Scholar 

  10. Mohammadi, F.: Numerical treatment of nonlinear stochastic Itô–Volterra integral equations by piecewise spectral-collocation method. J. Comput. Nonlinear Dyn. 14(3), 8 (2019)

    Google Scholar 

  11. Ke, T., Jiang, G., Deng, M.: Numerical solution of multidimensional stochastic Itô–Volterra integral equation based on the least squares method and block pulse function. Math. Probl. Eng. 2021, 10 (2021)

    Article  Google Scholar 

  12. Saffarzadeh, M., Loghmani, G., Heydari, M.: An iterative technique for the numerical solution of nonlinear stochastic Itô–Volterra integral equations. J. Comput. Appl. Math. 333, 74–86 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  13. Mirzaee, F., Hoseini, S.F.: Numerical approach for solving nonlinear stochastic Itô–Volterra integral equations using Fibonacci operational matrices. Sci. Iran. D 22(6), 2472–2481 (2015)

    Google Scholar 

  14. Saha Ray, S., Singh, P.: Numerical solution of stochastic Itô–Volterra integral equation by using shifted Jacobi operational matrix method. Appl. Math. Comput. 410, 16 (2021)

    MATH  Google Scholar 

  15. Saha Ray, S., Singh, S.: Numerical solutions of stochastic Volterra–Fredholm integral equations by Hybrid Legendre block-pulse functions. Int. J. Nonlinear Sci. Numer. Simul. 19(3–4), 289–297 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  16. Mirzaee, F., Hamzeh, A.: A computational method for solving nonlinear stochastic Volterra integral equations. J. Comput. Appl. Math. 306, 166–178 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  17. Fallahpour, M., Khodabin, M., Maleknejad, K.: Theoretical error analysis of solution for two-dimensional stochastic Volterra integral equations by Haar wavelet. Int. J. Appl. Comput. Math. 5(6), 13 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  18. Wen, X., Huang, J.: A Haar wavelet method for linear and nonlinear stochastic Itô–Volterra integral equation driven by a fractional Brownian motion. Stoch. Anal. Appl. 39(5), 926–943 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  19. Singh, S., Saha Ray, S.: “Stochastic operational matrix of Chebyshev wavelets for solving multi-dimensional stochastic Itô–Volterra integral equations’’. Int. J. Wavel. Multiresolution Inf. Process. 17(3), 1950007 (2019)

    Article  MATH  Google Scholar 

  20. Mirzaee, F., Alipour, S.: Quintic B-spline collocation method to solve n-dimensional stochastic Itô–Volterra integral equations. J. Comput. Appl. Math. 384, 9 (2021)

    Article  MATH  Google Scholar 

  21. Oksendal, B.: Stochastic Differential Equations, An Introduction with Applications, 5th edn. Springer-Verlag, New York (1998)

    MATH  Google Scholar 

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Singh, P.K., Saha Ray, S. A novel operational matrix method based on Genocchi polynomials for solving n-dimensional stochastic Itô–Volterra integral equation. Math Sci (2022). https://doi.org/10.1007/s40096-022-00502-z

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