Statistics of non-linear stochastic dynamical systems under L\'evy noises by a convolution quadrature approach

This paper describes a novel numerical approach to find the statistics of the non-stationary response of scalar non-linear systems excited by L\'evy white noises. The proposed numerical procedure relies on the introduction of an integral transform of Wiener-Hopf type into the equation governing the characteristic function. Once this equation is rewritten as partial integro-differential equation, it is then solved by applying the method of convolution quadrature originally proposed by Lubich, here extended to deal with this particular integral transform. The proposed approach is relevant for two reasons: 1) Statistics of systems with several different drift terms can be handled in an efficient way, independently from the kind of white noise; 2) The particular form of Wiener-Hopf integral transform and its numerical evaluation, both introduced in this study, are generalizations of fractional integro-differential operators of potential type and Gr\"unwald-Letnikov fractional derivatives, respectively.Comment: 20 pages, 5 figure

Optimal control of system governed by nonlinear volterra integral and fractional derivative equations

AbstractThis work presents a novel formulation for the numerical solution of optimal control problems related to nonlinear Volterra fractional integral equations systems. A spectral approach is implemented based on the new polynomials known as Chelyshkov polynomials. First, the properties of these polynomials are studied to solve the aforementioned problems. The operational matrices and the Galerkin method are used to discretize the continuous optimal control problems. Thereafter, some necessary conditions are defined according to which the optimal solutions of discrete problems converge to the optimal solution of the continuous ones. The applicability of the proposed approach has been illustrated through several examples. In addition, a comparison is made with other methods for showing the accuracy of the proposed one, resulting also in an improved efficiency

Legendre Wavelets Method for Solving Fractional Population Growth Model in a Closed System

A new operational matrix of fractional order integration for Legendre wavelets is derived. Block pulse functions and collocation method are employed to derive a general procedure for forming this matrix. Moreover, a computational method based on wavelet expansion together with this operational matrix is proposed to obtain approximate solution of the fractional population growth model of a species within a closed system. The main characteristic of the new approach is to convert the problem under study to a nonlinear algebraic equation

Shifted Legendre polynomial solutions of nonlinear stochastic Itô - Volterra integral equations

In this article, we propose the shifted Legendre polynomial-based solution for solving a stochastic integral equation. The properties of shifted Legendre polynomials are discussed. Also, the stochastic operational matrix required for our proposed methodology is derived. This operational matrix is capable of reducing the given stochastic integral equation into simultaneous equations with N+1 coefficients, where N is the number of terms in the truncated series of function approximation. These unknowns can be found by using any well-known numerical method. In addition to the capability of the operational matrices, an essential advantage of the proposed technique is that it does not require any integration to compute the constant coefficients. This approach may also be used to solve stochastic differential equations, both linear and nonlinear, as well as stochastic partial differential equations. We also prove the convergence of the solution obtained through the proposed method in terms of the expectation of the error function. The upper bound of the error in L² norm between exact and approximate solutions is also elaborately discussed. The applicability of this methodology is tested with a few numerical examples, and the quality of the solution is validated by comparing it with other methods with the help of tables and figures.Publisher's Versio

Collocation Orthonormal Berntein Polynomials method for Solving Integral Equations

In this paper, we use a combination of Orthonormal Bernstein functions on the interval  for degree ,and 6 to produce anew approach implementing Bernstein Operational matrix of derivative as a method for the numerical solution of linear Fredholm integral equations of the second kind and Volterra integral equations. The method converges rapidly to the exact solution and gives very accurate results even by low value of m. Illustrative examples are included to demonstrate the validity and efficiency of the technique and convergence of method to the exact solution. Keywords: Bernstein polynomials, Operational Matrix of Derivative, Linear Fredholm Integral Equations of the Second  Kind and Volterra Integral Equations