How Is Backpropagation Used In Artificial Neural Networks?
Kingsley Tagbo wrote: How Is Backpropagation Used In Artificial Neural Networks? [TABLE OF CONTENTS] Given a Feed Forward Neural Network with a backpropagation algorithm which uses an input layer I, one hidden layer H with two cells H1 and H2 and one output layer O with two cells O1 and O2 calculate the final weights and bias of the Neural Network after back propagation in one iteration of feed forward – back propagation cycle given the data below. Assume that the logistic sigmoid activation function F(x) = 1/( 1 – e-x ), was used in both the hidden and output layers. H1Output = 0.7, H2Output = 0.5, O1OutputTraining = 0.771, O2OutputTraining = 0.426, O1Output = 0.72, O2Output = 0.28, WH1O1 = 0.64, WH1O2 = 0.34, WH2O1 = 0.45, WH2O2 = 0.71, O1Bias = 0.54, O2Bias = -0.89 and Learning Rate = 0.4H1Output = output from cell H1 in the hidden layer.H2Output = output from cell H2 in the hidden layerO1OutputTraining = output from cell O1 in the output layer while training the neural networkO2Out
