Numerical Solutions of Fredholm Integral Equations Using Bernstein Polynomials (original) (raw)

A comparison of Numerical Solutions for Linear Fredholm Integral Equation of the Second Kind

Journal of Physics: Conference Series

The aim of this paper,we offereda new numerical methodwhich is Touchard Polynomials (T-Ps) for solving Linear Fredholm Integral Equation of the Second Kind (LFIE2-K), to find approximating Numerical Solution (N-S). At the beginning, we demonstrate (T-Ps) andconstruct the operational matrix which is a matrix representation for solution. The algorithm and someexamples are given; comparing the numerical results of proposed method with the numerical results of the other numerical method which is Bernstein Polynomials (B-Ps).Wewill show the high resolution of results by proposed method.The comparison between the Exact Solution(E-S) and the results of two methods are given by calculating absolute value of error and the Least Square Error (L.S.E).The results are calculated in Matlabcode.

Numerical approach based on Bernstein polynomials for solving mixed Volterra-Fredholm integral equations

AIP Advances, 2017

This paper provides an effective numerical technique for obtaining the approximate solution of mixed Volterra-Fredholm Integral Equations (VFIEs) of second kind. The VFIEs arise from parabolic boundary value problems, mathematical modelling of the spatio-temporal development of an epidemic, and from various physical and Engineering models. The proposed method is based on the discretization of VFIEs by Bernstein's approximation. Some results on convergence are also established which suggests that the technique converges to a smooth approximate solution. Its remarkable accuracy properties are finally demonstrated by several examples with graphical representation.

Numerical Approximation of Fredholm Integral Equation (Fie) of 2nd Kind using Galerkin and Collocation Methods

GANIT: Journal of Bangladesh Mathematical Society, 2019

In this research work, Galerkin and collocation methods have been introduced for approximating the solution of FIE of 2nd kind using LH (product of Laguerre and Hermite) polynomials which are considered as basis functions. Also, a comparison has been done between the solutions of Galerkin and collocation method with the exact solution. Both of these methods show the outcome in terms of the approximate polynomial which is a linear combination of basis functions. Results reveal that performance of collocation method is better than Galerkin method. Moreover, five different polynomials such as Legendre, Laguerre, Hermite, Chebyshev 1st kind and Bernstein are also considered as a basis functions. And it is found that all these approximate solutions converge to same polynomial solution and then a comparison has been made with the exact solution. In addition, five different set of collocation points are also being considered and then the approximate results are compared with the exact anal...

Computational Methods for Solving Fredholm Integral Equation of the Second Kind

2013

The main purpose of this paper is the numerical solution of the one-dimensional linear Fredholm integral equation of the second kind by the collocation and the Nystrom methods, using the Lagrange basis functions for piecewise linear interpolation. Some effective algorithms implementing these methods using the Matlab software have been constructed. The numerical results of test examples are also included to verify the performance of the proposed algorithms.

Numerical solution of linear integral equations system using the Bernstein collocation method

Advances in Difference Equations, 2013

Since in some application mathematical problems finding the analytical solution is too complicated, in recent years a lot of attention has been devoted by researchers to find the numerical solution of this equations. In this paper, an application of the Bernstein polynomials expansion method is applied to solve linear second kind Fredholm and Volterra integral equations systems. This work reduces the integral equations system to a linear system in generalized case such that the solution of the resulting system yields the unknown Bernstein coefficients of the solutions. Illustrative examples are provided to demonstrate the preciseness and effectiveness of the proposed technique. The results are compared with the exact solution by using computer simulations.

Numerical solution of some classes of integral equations using Bernstein polynomials

Applied Mathematics and Computation

This paper is concerned with obtaining approximate numerical solutions of some classes of integral equations by using Bernstein polynomials as basis. The integral equations considered are Fredholm integral equations of second kind, a simple hypersingular integral equation and a hypersingular integral equation of second kind. The method is explained with illustrative examples. Also, the convergence of the method is established rigorously for each class of integral equations considered here.

Numerical Solution of Nonlinear Fredholm Integrodifferential Equations by Hybrid of Block-Pulse Functions and Normalized Bernstein Polynomials

Abstract and Applied Analysis, 2013

In this paper, a numerical method to solve nonlinear Fredholm integral equations of second kind is proposed and some numerical notes about this method are addressed. The method utilizes Chebyshev wavelets constructed on the unit interval as a basis in the Galerkin method. This approach reduces this type of integral equation to solve a nonlinear system of algebraic equation. The method is also used to solve Fredholm integro-differential equation of second kind. Several numerical examples are presented to compare accuracy of Chebyshev wavelet Galerkin method with methods using polynomial Chebyshev basis.

A Bernstein polynomial approach for solution of nonlinear integral equations

The Journal of Nonlinear Sciences and Applications

In this study, a collocation method based on the generalized Bernstein polynomials is derivated for solving nonlinear Fredholm-Volterra integral equations (FVIEs) in the most general form via the quasilinearization technique. Moreover, quadratic convergence and error estimate of the proposed method is analyzed. Some examples are also presented to show the accuracy and applicability of the method.