Polynomial Interpolation in Matlab | Zendy

Siti Hawa Aziz | Zendy

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Polynomial Interpolation in Matlab

Author(s) -

Siti Hawa Aziz

Publication year - 2018

Publication title -

journal of engineering and science research

Language(s) - English

Resource type - Journals

ISSN - 2289-7127

DOI - 10.26666/rmp.jesr.2018.4.3

Subject(s) - polynomial interpolation , interpolation (computer graphics) , lagrange polynomial , matlab , trigonometric interpolation , birkhoff interpolation , inverse quadratic interpolation , mathematics , spline interpolation , polynomial , function (biology) , graph , nearest neighbor interpolation , set (abstract data type) , data point , linear interpolation , mathematical optimization , computer science , algorithm , discrete mathematics , mathematical analysis , bilinear interpolation , animation , computer graphics (images) , statistics , evolutionary biology , biology , operating system , programming language

The problem of constructing such a continuous function is called data fitting. Many times, data given only at discrete points. With interpolation, we seek a function that allows us to approximate f(x) such that functional values between the original data set values may be determined. The process of finding such a polynomial is called interpolation and one of the most important approaches used are Lagrange interpolating formula. In this study, researcher determining the polynomial interpolation by using Lagrange interpolating formula. Then, a mathematical modelling was built by using MATLAB programming to determine the polynomial interpolation for a given points using the Lagrange method. The result of the study showed that the manual calculating and the MATLAB mathematical modelling will give the same answer for evaluated x and graph.

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