High Order Neural Networks for Efficient Associative Memory Design

Part of Neural Information Processing Systems 0 (NIPS 1987)

Bibtex Metadata Paper


Gérard Dreyfus, Isabelle Guyon, Jean-Pierre Nadal, Léon Personnaz


We propose learning rules for recurrent neural networks with high-order interactions between some or all neurons. The designed networks exhibit the desired associative memory function: perfect storage and retrieval of pieces of information and/or sequences of information of any complexity.