Consider the following neural network classifying the input vectors to -1 and +1 classes using the hard limiter activation function. 1) 11'3.1 W3.2 W4.1 W43 4 y 3 2 W4.2 a) Run the network with X' X3 weights as 1's and the activation functions as hard limiters. b) Consider an unknown input pattern X' = using all the is tested in this neural network with memory based learning rule using 3-nearest neighbour rule. Assume that the network has a memory of the learned patterns listed in part (a). Derive the input (x1,x2) plane, and compute the class of the unknown pattern as -1 or +1 by using memory based learning. Ac Go