2. Apply the back propagation algorithm for the given layer network. Calculate the value of error signal in the given MLP were xl = 1.5, x2 = -2.3, wl=1, w2 = -2.8, w3 = -1.6, w4 = 2, br= -1 and sigmoid as activation function for each neuron. N N Output N

Compute the capacity and input distribution attaining it for the discrete memoryless channel X → Y with X = y = {0, 1, 2, 3} given by Y = X + Z mod 4, where Z takes on values from Z = {0, 1, 2, 3} with z(0) = 1/2, z(1) = 0, and z(2) = z(3) = 1/4.

In a perceptron network there are two inputs and two synaptic weights. (CLO 2.1)Classify the perceptron is Class 1 or Class 2 using decision boundary.Input Weights BiasX1 -2 W1 1.5 B 1X2 -2.7 W2 1.8Find the given inputs (-3, 7) lies above line or below line in the quadratic equation 4x +2y - 15.