Mohammadi, Fakhrodin Second kind Chebyshev wavelet Galerkin method for stochastic Itô-Volterra integral equations. (English) Zbl 1359.65015 Mediterr. J. Math. 13, No. 5, 2613-2631 (2016). Using a stochastic operational matrix for the second kind Chebyshev wavelets used as a basis, a Galerkin approximation scheme is devised to obtain numerical approximations for the solution of an Itô stochastic Volterra integral equation of the form \[ X(t)= f(t)+ \int^t_0 \alpha(s, X(s))\,ds + \int^t_0 \sigma(s,X(s))\,dB(s),\quad t\in[0,T), \] where \(B(t)\) is a Brownian motion process. \(L^2\) convergence of the approximate solutions to the exact solution is proved. For three examples numerical results from this method are compared with the exact solution and with results from other numerical methods to illustrate the accuracy and efficiency of this method. Reviewer: Melvin D. Lax (Long Beach) Cited in 10 Documents MSC: 65C30 Numerical solutions to stochastic differential and integral equations 65T60 Numerical methods for wavelets 60H20 Stochastic integral equations 60H35 Computational methods for stochastic equations (aspects of stochastic analysis) 45R05 Random integral equations Keywords:second kind Chebyshev wavelets; Itô integral; stochastic operational matrix; stochastic Itô-Volterra integral equations; Brownian motion; numerical results × Cite Format Result Cite Review PDF Full Text: DOI References: [1] Kloeden P.E., Platen E.: Numerical Solution of Stochastic Differential Equations. Springer-Verlag, Berlin (1999) · Zbl 0752.60043 [2] Oksendal B.: Stochastic Differential Equations: An Introduction with Applications. Springer, New York (1998) · Zbl 0897.60056 [3] Higham D.J.: An algorithmic introduction to numerical simulation of stochastic differential equations. 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