Consider the following Multi$-$Layer Perceptron with the given input and output values of one instance with the associated weights. Use the Sigmoid function, $f(x)=\frac{1}{1+e^{-x}},$ for activation function. $($Use $4-$decimal places for your calculations.$)$

$1$

b$1.35$

$1$

b$260$

a$)$ Find the input and output for $o_1$ and $o_2.$

b$)$ Find the error by using Squared Error Function, i$.$e$.{}_2^1($ actual value $-$ predicted value ${)}^2.$

c$)$ Update the value of $w_5$ by using Back Propagation.