High Order Neural Networks for Efficient Associative Memory Design

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

Abstract: 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.