* Feedforward Neural Networks – This is the most common type of neural network architecture, with the first layer being the input layer and the last layer being the output layer. All middle layers are hidden layers.
* Recurrent Neural Network – This network architecture is a series of ANNs in which connections between nodes form a directed graph along a temporal sequence. Therefore, this type of network exhibits dynamic behavior over time.
* Symmetrically Connected Neural Networks – These are similar to recurrent neural networks, with the only difference being that the connections between units are symmetric in symmetrically connected neural networks (i.e. same weight n both directions).
