Question: The layers of an RBF $($Radial Basis Function$)$ artificial neural network are defined as $1-2-1$

neurons. Weights matrix of the input layer and bias values ;

$W^1=\left[\begin{array}{c}-1\\ 1\end{array}\right],b^1=\left[\begin{array}{c}0\mathrm{.}5\\ 0\mathrm{.}5\end{array}\right]$

given as$.$ The bias value of the second layer is $b=0$ and the training input values are ;

$\{p_1=1,t_1=-1\},\{p_2=0,t_2=0\},\{p_3=-1,t_3=1\}$

will be used. Calculate the weights of the second layer using least squares $($regularization coefficient

use $=0).$