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PNN often use in classification problems<ref>http://www.mathworks.in/help/toolbox/nnet/ug/bss38ji-1.html</ref>.When an Input is present, first layer computes the distance from the input vector to the training input vectors. It produce a vector where its elements indicate how close the input is to training input. The second layer sums the contribution for each class of inputs and produce it's net output as a vector of probabilities.Finally, a compete transfer function on the output of the second layer picks the maximum of these probabilities, and produces a 1 for that class and a 0 for the other classes.
http://radio.feld.cvut.cz/matlab/toolbox/nnet/07_grnn.gif
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