Consider the neural network shown below. $x1$ and $x2$ are the input of the Neural Network, h$1$ and h$2$ are the nodes of the hidden layer, $01$ and $02$ display the outputs, $b1$ and $b2$ are the bias nodes.

$w1=0\mathrm{.}25$;$w2=0\mathrm{.}28$;$w3=0\mathrm{.}35$;$w4=0\mathrm{.}15$;$w5=0\mathrm{.}35$;$w6=0\mathrm{.}2$;$w7=0\mathrm{.}45$;$w8=0\mathrm{.}4$

$b1=0\mathrm{.}45b2=0\mathrm{.}5$

What happens if we pass in the input $x=[0\mathrm{.}1,0\mathrm{.}2]?$ The activation function is the sigmoid function as below:

$f(z)=\frac{1}{1+e^{-z}}$ please give a step by step correct answer with all explanationIn