$\%$ Objective Function to be minimized

function f $=$ f$($x$,$ y$,$ z$)$

f $=100*$x$^2+$ y$^2+0\mathrm{.}1*$z$^2+$ x$*$y $+0\mathrm{.}1*$x$*$y $-6*$x $+4*$y $+6*$z $+15$;

end

$\%$ Gradient of the function

function g $=$ grad$($x$,$ y$,$ z$)$

g $=[200*$x$+$y$-6,2*$y $+$ x $+0\mathrm{.}1*$z $+4,0\mathrm{.}2*$z $+0\mathrm{.}1*$y $+6]$;

end

$\%$ Step size for the gradient descent

alpha $=0\mathrm{.}1$;

$\%$ Maximum number of iterations

maxIter $=100$;

$\%$ Stopping criteria

epsilon $=1$e$-4$;

$\%$ Starting point

x$0=[10,10,10]$;

$\%$ Current point

x $=$ x$0$;

$\%$ Previous point

xPrev $=$ zeros$($size$($x$0))$;

$\%$ Iteration counter

k $=0$;

$\%$ Gradient descent loop

while k $<$ maxIter && euclideanNorm$($x$,$ xPrev$)>$ epsilon

$\%$ Update the previous point

xPrev $=$ x;

$\%$ Compute the gradient at the current point

g $=$ grad$($x$(1),$ x$(2),$ x$(3))$;

$\%$ Update the current point

x$(1)=$ x$(1)-$ alpha $*$ g$(1)$;

x$(2)=$ x$(2)-$ alpha $*$ g$(2)$;

x$(3)=$ x$(3)-$ alpha $*$ g$(3)$;

$\%$ Increase the iteration counter

k $=$ k $+1$;

end

$\%$ Print the result

disp$([\text{'}$Local optima: $\text{'},$ num$2$str$($x$)])$;

$\%$ Euclidean norm

function n $=$ euclideanNorm$($x$,$ y$,$ z$)$

n $=$ sqrt$($sum$(($x $-$ y$)-$z$).^2)$;

end

What is the error here, I want to output the local minima of objective function