$1-$ A relatively advanced Al flight control system employs a Principal Component Analysis $($PCA$)$ algorithm to create a two$-$dimensional matrix from a variety of features to be used for an Atypical Approach Detection $($AAD$)$ system. Your role is to develop a MATLAB function to find the root of PCADATA attached, to be used in an embedded optimization parent code.

In the M$.$file, import the PCADATA using xIsread$(\text{'}$filename$\text{'}).$ Create $f(x)$ from data using two methods: $1-$ Interpolation $($you can use interp$1$ function of MATLAB$),$ and $2-$ Trend line $($you can use Trendline of excel to create a polynomial of degree $6$ from the data$)$

a$)$ Develop a MATLAB function using Muller's method to find the root of the datadriven function $f(x)$ and enter the results in the below table. Upload two MATLAB files; one function and one $M,$ file to call the function. All the files must start with the student's initials and include the root finding method $($in this case Muller's$)$

$(6$ marks$)$

Table $1$: Muller's Method Results

$\backslash$table$[[f(x)$ Type,No$.$ of Iterations to Convergence,Root of $f(x),$Error $E_n^{**}$