IN MATLAB Write a MATLAB function that can be used by a user to perform polynomial...
Write a MATLAB function that can be used by a user to perform polynomial interpolation using Lagrange Interpolation Method on a set of data.
matlab The error function is a mathematical function that frequently arises in probability and statistics. It also can show up in the solution to some partial differential equations, particularly those arising in heat and mass transfer applications. The error function is defined as 2 e-t dt picture attached This function is actually built-in to MATLAB as the command erf, and here we'll use that function to compute a "true value" with which we can compare results of two interpolation approaches....
Create a MATLAB function to perform Lagrange Interpolation. Your function will be used as illustrated below: >> ya = Lagrange(x, y, a) where "x" is a vector of ? independent data values, "y" is a vector of ? dependent function values corresponding to "x", "a" is an arbitrary value of "x" for which you want to know the Westimate of "y", and "ya" is the estimate of the function at x=a. Print an error message and exit the function if...
matlab code Task 2 (30 points +4 for comments): Write computer code that uses Lagrange's nterpolating Polynomials to fit an interpolating polynomial to the data for Task 2 in the excel file and use the polynomials to interpolate the data set and evaluate the function value at x values of 8.4, 7.6, and 6.7 What are the first through 3rd order estimations for the interpolated function value at> 8.4 and x 7.6? a) b) Extrapolate the data set to determine...
Please solve problem 7 not 5. however you need data from problem 5 to slove problem 7 Hide email Problem 5 (10 points): For the data below, perform Newton Divided Difference interpolation of fC7.5 C) using first through third order interpolating polynomial:s for f viscosity of water 1000 in metric (MKS) units. Choose thexi interpolation points to provide the most accurate interpolation (points should most closely surround x = 7.5 C). 040 y i 1.781 | İ .568 | 1...
matlab matlab For this problem you will test a few interpolation approaches for the application of generating interpolated data. We'll do this by interpolating data that is sampled from a known mathematical function. The same function can then be used to compute true values at the interpolated points to use in error Consider the following mathematical function (Runge's function): 1+25r2 Write a function mfile that uses this formula to generate a set of data use those points along approaches outlined...
Problem 5 (programming): Create a MATLAB function named lagrange interp.m to perform interpolation using Lagrange polynomials. Download the template for function lagrange interp.m. The tem Plate is in homework 4 folder utl TritonED·TIue function lakes in the data al nodex.xi and yi, as well as the target x value. The function returns the interpolated value y. Here, xi and yi are vectors while x and y are scalars. You are not required to follow the template; you can create the...
B.1 Write a MATLAB user-defined function for interpolation with linear splines Name the function Yint = Linear Splines, y, rint), where the input ar- guments and y are vectors with the coordinates of the data points and rint is the coordinate of the interpolated point. The output argument Yint is the y value of the interpolated point. Also write a program in a script file that plots the data points and the curve of the Linear splines that interpolates the...
Please use matlab, post the code, and dont just write the code by hand. Thank you! 4 [3 points] Use the function f(x on the interval [5, 5] and the 11 points below to find a N-10 Lagrange polynomial, using MATLAB. You will need to write code for and plot the polynomial as a function of x, but you do not have to write the polynomials down by hand 5 0 2 3 4 5 f(x) | 0.0399 | 00623...
Consider polynomial interpolation of the function f(x)=1/(1+25x^2) on the interval [-1,1] by (1) an interpolating polynomial determined by m equidistant interpolation points, (2) an interpolating polynomial determined by interpolation at the m zeros of the Chebyshev polynomial T_m(x), and (3) by interpolating by cubic splines instead of by a polynomial. Estimate the approximation error by evaluation max_i |f(z_i)-p(z_i)| for many points z_i on [-1,1]. For instance, you could use 10m points z_i. The cubic spline interpolant can be determined in...