If we have a neural network such as the multilayer perceptron back propagation neural network that uses sigmodial logistic activation functions is it possible to feed the network outputs and have it compute back a set of inputs? Since we can reverse the activation function by using the natural logarithm and inverse operations until we have a sum value that is made up of all the weights multiplied by their inputs i would think that it would be possible to at least get sets of possible inputs that will generate the specified output value.
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