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Neural Network & Fuzzy Systems
Hidden Layer
Introduction:-Back-propagation is simply a way to determine the error values in hidden layers. This needs be done in order to update the weights.
The best example to explain where back-propagation can be used is the XOR problem.
Consider a simple graph shown below.
− All points on the right side of the line are ve, therefore the output of the neuron should be ve.
− All points on the left side of the line are –ve, therefore the output of the neuron should be –ve.
Training a network to operate as an AND switch can be done easily through only one neuron.
But a XOR problem can't be solved using only one neuron. If we want to train an XOR, we need 3 neurons, fully-connected in a feed-forward network as shown below.