递归神经网络（RNN）是两种人工神经网络的总称。一种是时间递归神经网络（recurrent neural network），另一种是结构递归神经网络（recursive neural network）。时间递归神经网络的神经元间连接构成有向图，而结构递归神经网络利用相似的神经网络结构递归构造更为复杂的深度网络。RNN一般指代时间递归神经网络。单纯递归神经网络因为无法处理随着递归，权重指数级爆炸或消失的问题（Vanishing gradient problem），难以捕捉长期时间关联；而结合不同的LSTM可以很好解决这个问题。

A recurrent neural network (RNN) is a class of artificial 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. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. This makes them applicable to tasks such as unsegmented connected handwriting recognition or speech recognition.