In a feed$-$forward neural network with the following specifications:

The input layer has $4$ neurons, the hidden layer has $3$ neurons, and the output layer has $2$ neurons using the sigmoid activation function for given input values $[0\mathrm{.}5,0\mathrm{.}8,0\mathrm{.}2,0\mathrm{.}6]$ as well as the initial weights for the connections.

W$1$: $[0\mathrm{.}1,0\mathrm{.}3,0\mathrm{.}5,0\mathrm{.}2]$

W$2$: $[0\mathrm{.}2,0\mathrm{.}4,0\mathrm{.}6,0\mathrm{.}2]$ Input layer to hidden layer weights W$3$: $[0\mathrm{.}3,0\mathrm{.}5,0\mathrm{.}7,0\mathrm{.}2]$

W$4$: $[0\mathrm{.}4,0\mathrm{.}1,0\mathrm{.}3]$

W$5$: $[0\mathrm{.}5,0\mathrm{.}2,0\mathrm{.}4]$ Hidden layer to output layer weights

What is the output of the output layer when the given input values are passed through the neural network? Round the answer to two decimal places:

$.[0\mathrm{.}92,0\mathrm{.}98]$

$$b$.[0\mathrm{.}72,0\mathrm{.}78]$

$.[0\mathrm{.}62,0\mathrm{.}68]$

$$d$.[0\mathrm{.}82,0\mathrm{.}88]$