I start to learn artificial neural network and all introduction that I have found on internet present architecture with a number of input variable, so the input layer has the same number of neurons as number of variable. Then a number of neurons in hidden layers and only one output neurons. Does it make sense to have several output neurons ? Is it the same method but with more neurons at the end ? I have try to do some tests in fortran90, starting from a basic example, but I start to get confused to make it with more than one output neurons Thanks  EDITTo be more clear : is there a way to create an ANN with various output neurons that can take different states ? (without making a correspondence between K class corresponding to each possible output)I would like to have 3 output neurons that will take the following states :Inputs X  |  Outputs Y----------------------0 0 0 1 0 |   0 0 01 0 0 1 1 |   1 1 01 1 0 1 1 |   0 1 11 0 0 0 1 |   1 1 10 0 0 0 0 |   1 0 0if yes what is the methods ? 
create a ANN with more than one neuron output
machine learning;neural networks
It's possible to have more than one neuron in the output. The  softmax function is used for that purpose. With this function, the output may have $K$ classes. If we have a network with $K = 3$ output classes, and some input shall belong to class $k = 1$, for example, the desired output would be: $[1 0 0]$. If another input shall belong to class $k = 2$, then the desired output would be $[0 1 0]$. And so on.