From the following code given solve the question.

Now lets use the MATLAB M-file in the text. You can use that as a starting point or write your own code following the pseudo-code provided. Write a MATLAB function y = func2(x) which implements the equation ( ) = -.9 ² +1.7x + 2.5 = 0. It will be used by the Newton-Raphson method M file. Use the MATLAB implementation of Newton-Raphson method to find a root of the function ( ) = -.9 ² +1.7x + 2.5 = 0 with the initial guess x0 = 5. Perform the computations until percentage approximate relative error (e_a (%)) is less than e_a = 2%. You are required to fill the following table.

Iteration	Xi	F(xi)	F(xi)	Eai(%)
0		-11.5	-7.3
1
2
3
4

matlabcode

function [root,eaf,iter]=newtraph(xr,es,maxit)

% newtraph: NewtonRaphson root location zeroes

% [root,ea,iter]=newtraph(func,dfunc,xr,es,maxit,p1,p2,...):

% uses NewtonRaphson method to find the root of func

% input:

func = @(x)-0.9*x^2 + 1.7*x + 2.5;

dfunc = @(x) -1.8*x + 1.7;

% xr = initial guess

% es = desired relative error (default = 0.0001%)

% maxit = maximum allowable iterations (default = 50)

% p1,p2,... = additional parameters used by function

% output:

% root = real root

% ea = approximate relative error (%)

% iter = number of iterations

if nargin<3,error('at least 3 input arguments required'),end

if nargin<4||isempty(es),es=0.0001;end

if nargin<5||isempty(maxit),maxit=50;end

eaf(1)=0;

iter = 0;

while (1)

xrold = xr;

xr = xr - func(xr)/dfunc(xr);

iter = iter + 1;

if xr ~= 0, ea = abs((xr - xrold)/xr) * 100; end

if ea <= es || iter >= maxit, break, end

eaf(iter)=ea;

fx=-0.9*5^2 + 1.7*5 + 2.5

df= -1.8*5 + 1.7

end

root = xr;

disp("")