Consider the neural network shown bolow, $x1$ and $x2$ are the input of the Nourd

Notwork, it and h$2$ ere the nodes of the hidden layer, o$1$ and $2$ d diepley the outputs.

b$1$ and b$2$ ere the bias nodes.

$w=0\mathrm{.}25$;$w2=0\mathrm{.}28$;$w3=0\mathrm{.}35$;$w4=0\mathrm{.}15$;$w5=0\mathrm{.}35$;$w6=0\mathrm{.}2$;$w7=0\mathrm{.}45$;$w0=0\mathrm{.}4$

b$1=0\mathrm{.}45$ b$2=0\mathrm{.}5$

What happens if we pass in the input $x=[0\mathrm{.}1,0\mathrm{.}2]$ The ectivation function is the

slomold finction as below:

$f(z)=\frac{1}{1+e^{-1}}$