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Many neurons or processing elements are interconnected to form a parallel neurocomputing network. Each element or neuron is a very simple processor that carries out the pondered sum of its inputs and applies them to a function (linear, sigmoidea) to generate an output that is sent to another neuron. The most usual type of ANN is the feedforward multilayer one, where no information is fed back during the recall process. Feedback signals are used only during the training of the neural network. Generally, the backpropagation method is used for adjusting the neural network weights during the training...
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