The following RBF network uses Gaussian activation functions in the hidden layer and linear activation function in the output layer. Suppose the Gaussians are centered at [0, 0] (neuron 1) and [3, 3] (neuron 2) and have variances of 1.5 and 2, respectively given the weight vector w = [3, 2, 315. compute the output y when an input x = [1, 1]T is applied to the network. 1 WO I wi y 2 W2 Gaussian(activation.function) = V27o? The following RBF network uses Gaussian activation functions in the hidden layer and linear activation function in the output layer. Suppose the Gaussians are centered at [0, 0] (neuron 1) and [3, 3] (neuron 2) and have variances of 1.5 and 2, respectively given the weight vector w = [3, 2, 315. compute the output y when an input x = [1, 1]T is applied to the network. 1 WO I wi y 2 W2 Gaussian(activation.function) = V27o