Recurrent Neural Network

Recurrent Neural Networks – RNNs – are a class of artificial neural network where connections between nodes form a directed graph along a sequence. This characteristic allows RNNs to exhibit dynamic temporal behavior for a time sequence.

Diagram for a recurrent neural network
A diagram for a one-unit recurrent neural network. From bottom to top : input state, hidden state, output state. U, V, W are the weights of the network. Compressed diagram on the left and the unfold version of it on the right.

Unlike feedforward neural networks, RNNs can use their internal state (memory) to process sequences of inputs. This makes them applicable to tasks such as unsegmented, connected handwriting recognition or speech recognition.

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