Different from regular neural networks (including deep neural networks), recurrent neural networks (RNN) provides a representation that connects a sequence of inputs. It could a time sequence, a DNA sequence, or any other sequence. A regular NN takes one input (a vector) at a time and the output responds to the input alone, not the previous inputs or the future inputs. RNN would allow the output to be related to the current input along with the previous inputs or the future inputs.
Let’s consider a simple RNN that takes a sequence of two inputs.