Recurrent Multilayer Perceptron Network

A Recurrent Multilayer Perceptron Network is a Recurrent Neural Network composed of cascaded subnetworks.

• Example(s):
  • …
• Counter-Example(s):
  • a Bidirectional Associative Memory (BAM) Network,
  • a DAG Recurrent Neural Network,
  • an Echo State Network,
  • an Elman Network,
  • a Gated Recurrent Unit (GRU) Network,
  • a Hopfield Recurrent Neural Network,
  • a Jordan Network,
  • a Long Short-Term Memory (LSTM) Network.
• See: Artificial Neural Network, Cascade-Correlation Network.

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References

2018

• (Wikipedia, 2018) ⇒ https://en.wikipedia.org/wiki/Recurrent_neural_network#Recurrent_multilayer_perceptron_network Retrieved:2018-3-4.
  • Generally, a Recurrent Multi-Layer Perceptron (RMLP) network consists of cascaded subnetworks, each of which contains multiple layers of nodes. Each of these subnetworks is feed-forward except for the last layer, which can have feedback connections. Each of these subnets is connected only by feed forward connections.

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