Up until know I only used neural networks to classify a single output, I set one output neuron for each class and check which neuron has the highest/lowest activation.
What I am trying to do is to detect a pattern and instead of outputting a single value (either class or activation value) I would like to output multiple values. eg,
[0,5 0,5 0,5] -> [0,5 0,5 0,5] [1 1 1] -> [1 1 1] [2 2 2] -> [-1 -1 -1]
So what I am wondering is can I use a network with 3 outputs and instead of checking activation, use all outputs as my output pattern?