Each training example in the network passing through the calculation twice: once to move the spread of computing, from the beginning of input layer, transmission floors and processed to produce an output, and a the actual output and the difference between the desired output error vector again to reverse the spread of computing, from the output layer to the input layer, using error vector values of the right to amend the layers. BP algorithm has a strong mathematical foundation, dramatically expanded the use of neural networks, resulting in a number of successful examples of application of neural network research have a significant role in the rise once again.

neural-network-back-propagation-algorithm.m

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