Recurrent neural network

A recurrent neural network (RNN) is a class of neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior.
Recurrent neural networks must be approached differently from feedforward neural networks, both when analyzing their behavior and training them. Recurrent neural networks can also behave chaotically. Usually, dynamical systems theory is used to model and analyze them. While a feedforward network propagates data linearly from input to output, recurrent networks (RN) also propagate data from later processing stages to earlier stages.