Let TOk represents the target output of k-th neuron lying on the output layer

Let TOk represents the target output of k-th neuron lying on the output layer. The error in prediction at k-th output neuron corresponding to a particular training scenario can be calculated as follows: Ek = 1 2 (TOk − OOk) 2. (10.6) For a training scenario, the error in prediction considering all output neurons can be determined like the following: E = P k=1 1 2 (TOk − OOk) 2, (10.7) where P represents the number of output neurons. The total error in prediction for all output neurons can be determined considering all training scenarios as follows: Etot = L l=1 P k=1 1 2 (TOkl − OOkl) 2, (10.8) where L indicates the number of training scenarios.


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