Use McCulloch -Pitts neuron model to design logic network for the following function y=x1x2x3 (A prime...

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Use McCulloch -Pitts neuron model to design logic network for the following function y=x1x2x3 (A prime (') denotes a logical complement). Assume that y=1 for Ex 2T where T is a threshold value. b) Use McCulloch -Pitts neuron model to design logic network for solving the XOR by constructing (a) decision regions, and (b) a truth table for the network. c) Fig.1 shows a neural network involving a single hidden neuron for solving the XOR problem; this network is not a standard multilayer perceptron and may be viewed as an alternative. Show that the network of Fig. 1 solves the XOR problem by constructing (a) decision regions, and (b) a truth table for the network. d) Use the back-propagation algorithm for computing a set of synaptic weights and bias levels for the standard neural network to solve the XOR problem. Assume to use of a logistic function for the nonlinearity. Choose the structure (for example one hidden layer with three neurons) and explain updating mechanism through the backpropagation algorithm for one epoch. Inputs 1.5 Figure 1. -0.5 Output Ac Go Use McCulloch -Pitts neuron model to design logic network for the following function y=x1x2x3 (A prime (') denotes a logical complement). Assume that y=1 for Ex 2T where T is a threshold value. b) Use McCulloch -Pitts neuron model to design logic network for solving the XOR by constructing (a) decision regions, and (b) a truth table for the network. c) Fig.1 shows a neural network involving a single hidden neuron for solving the XOR problem; this network is not a standard multilayer perceptron and may be viewed as an alternative. Show that the network of Fig. 1 solves the XOR problem by constructing (a) decision regions, and (b) a truth table for the network. d) Use the back-propagation algorithm for computing a set of synaptic weights and bias levels for the standard neural network to solve the XOR problem. Assume to use of a logistic function for the nonlinearity. Choose the structure (for example one hidden layer with three neurons) and explain updating mechanism through the backpropagation algorithm for one epoch. Inputs 1.5 Figure 1. -0.5 Output Ac Go