10.1007/s40096-022-00502-z

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

  1. Department of Mathematics, National Institute of Technology, Rourkela, 769008, IN

Published in Issue 2022-12-17

How to Cite

Singh, P. K., & Saha Ray, S. (2022). A novel operational matrix method based on Genocchi polynomials for solving n-dimensional stochastic Itô–Volterra integral equation. Mathematical Sciences, 18(2 (June 2024). https://doi.org/10.1007/s40096-022-00502-z

Abstract

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.

Keywords

  • Genocchi polynomial,
  • Stochastic Itô–Volterra integral equations,
  • Itô integral,
  • Operational matrices,
  • Convergence analysis

References

  1. Nemati and Ordokhani (2013) “Legendre expansion methods for the numerical solution of nonlinear 2D Fredholm integral equations of the second kind (pp. 609-621) https://doi.org/10.14317/jami.2013.609
  2. Isah et al. (2017) Collocation method based on Genocchi operational matrix for solving generalized fractional pantograph equations
  3. Behera and Saha Ray (2021) Euler wavelets method for solving fractional-order linear Volterra–Fredholm integro-differential equations with weakly singular kernels 40(6) https://doi.org/10.1007/s40314-021-01565-9
  4. Isah and Phang (2019) New operational matrix of derivative for solving non-linear fractional differential equations via Genocchi polynomials 31(1) (pp. 1-7) https://doi.org/10.1016/j.jksus.2017.02.001
  5. Dehestani et al. (2020) The novel operational matrices based on 2D-Genocchi polynomials: solving a general class of variable-order fractional 39(4) https://doi.org/10.1007/s40314-020-01314-4
  6. Sweilam et al. (2017) New spectral second kind Chebyshev wavelets scheme for solving systems of integro-differential equations 3(2) (pp. 333-345) https://doi.org/10.1007/s40819-016-0157-8
  7. Khajehnasiri (2016) Numerical solution of nonlinear 2D Volterra–Fredholm integro-differential equations by two-dimensional triangular function 2(4) (pp. 575-591) https://doi.org/10.1007/s40819-015-0079-x
  8. He et al. (2021) Improved block-pulse functions for numerical solution of mixed Volterra–Fredholm integral equations 10(3) https://doi.org/10.3390/axioms10030200
  9. He (2020) A simple approach to Volterra–Fredholm integral equations 6(Special Issue) (pp. 1184-1186)
  10. Mohammadi (2019) Numerical treatment of nonlinear stochastic Itô–Volterra integral equations by piecewise spectral-collocation method 14(3)
  11. Ke et al. (2021) Numerical solution of multidimensional stochastic Itô–Volterra integral equation based on the least squares method and block pulse function https://doi.org/10.1155/2021/6662604
  12. Saffarzadeh et al. (2018) An iterative technique for the numerical solution of nonlinear stochastic Itô–Volterra integral equations (pp. 74-86) https://doi.org/10.1016/j.cam.2017.09.035
  13. Mirzaee and Hoseini (2015) Numerical approach for solving nonlinear stochastic Itô–Volterra integral equations using Fibonacci operational matrices 22(6) (pp. 2472-2481)
  14. Saha Ray and Singh (2021) Numerical solution of stochastic Itô–Volterra integral equation by using shifted Jacobi operational matrix method
  15. Saha Ray and Singh (2018) Numerical solutions of stochastic Volterra–Fredholm integral equations by Hybrid Legendre block-pulse functions 19(3–4) (pp. 289-297) https://doi.org/10.1515/ijnsns-2017-0038
  16. Mirzaee and Hamzeh (2016) A computational method for solving nonlinear stochastic Volterra integral equations (pp. 166-178) https://doi.org/10.1016/j.cam.2016.04.012
  17. Fallahpour et al. (2019) Theoretical error analysis of solution for two-dimensional stochastic Volterra integral equations by Haar wavelet 5(6) https://doi.org/10.1007/s40819-019-0739-3
  18. Wen and Huang (2021) A Haar wavelet method for linear and nonlinear stochastic Itô–Volterra integral equation driven by a fractional Brownian motion 39(5) (pp. 926-943) https://doi.org/10.1080/07362994.2020.1858873
  19. Singh and Saha Ray (2019) “Stochastic operational matrix of Chebyshev wavelets for solving multi-dimensional stochastic Itô–Volterra integral equations” 17(3) https://doi.org/10.1142/S0219691319500073
  20. Mirzaee and Alipour (2021) Quintic B-spline collocation method to solve n-dimensional stochastic Itô–Volterra integral equations https://doi.org/10.1016/j.cam.2020.113153
  21. Oksendal (1998) Springer-Verlag