Hebbian Learning is used to train the neuron shown below. The "learning" is characterized by the weight

vectors shown.

$($a$)$ Complete the training table.

$($b$)$ Transcribe the bipolar notation to binary notation and fill out the function table.

$($c$)$ Did this neuron learn the function? How can you tell?

$f(y_{-}in)=\{\begin{array}{ccc}1& ify{?}_{(}()i)n& >0\\ -1& if{y}_{i}n& 0\end{array}$

Initial weights: ${\left[\begin{array}{ccc}0& 0& 0\end{array}\right]}^{TT}$

Next iteration: ${\left[\begin{array}{ccc}1& -1& -1\end{array}\right]}^{TT}$

Next iteration: ${\left[\begin{array}{ccc}0& 0& -2\end{array}\right]}^{TT}$

Next iteration: ${\left[\begin{array}{ccc}-1& -1& -1\end{array}\right]}^{TT}$

Final weights: ${\left[\begin{array}{ccc}-2& -2& -2\end{array}\right]}^{TT}$

$($a$)$