Consider recursive feedforward deep ANN with one input layer, $700$ hidden layers and one output layer. $[$An example of much simpler recursive ANN with only THREE hidden layersis shown in Figure.$]$

Assume, the same sets of weights and biases for ALL nodes of the ANN.

Use the following data $($pay attention to the signs in numbers$)$:

$*$ recursive given weights: w$11=0\mathrm{.}3$; w$12=0\mathrm{.}6$; w$21=0\mathrm{.}2$; w$22=0\mathrm{.}8$;

$*$ recursive given biases: b$1=14$; b$2=2$;

$*$ given inputs: x$1=1$; x$2=2.$

For simplicity, assume, that the recursive activation function for each node is an identity function, i$.$e$.$ a linear function with UNIT coefficient: g$($x$)=$x$.$

Determine the value of y$2$ the second output of this deep ANN.

write a matlab code to solve this problem