The training algorithm stops when a specified condition is satisfied. Some stopping criteria commonly used are:
Refer to the figure that illustrates the backpropagation multilayer network with layers. represents the number of neurons in th layer. Here, the network is presented the th pattern of training sample set with -dimensional input and -dimensional known output response . The actual response to the input pattern by the network is represented as . Let be the output from the th neuron in layer for th pattern; be the connection weight from th neuron in layer to th neuron in layer ; and be the error value associated with the th neuron in layer .