Open AccessPolynomial Interpolation in Matlab
Author(s) -
Siti Hawa Aziz,
Politeknik Ungku Omar
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 , trigonometric interpolation , matlab , birkhoff interpolation , inverse quadratic interpolation , mathematics , spline interpolation , polynomial , function (biology) , nearest neighbor interpolation , data point , linear interpolation , algorithm , computer science , mathematical optimization , bilinear interpolation , mathematical analysis , animation , computer graphics (images) , statistics , evolutionary biology , biology , operating system
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.