Storing sequences in binary tournament-based neural networks

Claude Berrou; Michael Rabbat; Vincent Gripon; Xiaoran Jiang

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Storing sequences in binary tournament-based neural networks

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arxiv 1409.0334 v1 pith:C2LT3UFE submitted 2014-09-01 cs.NE

Xiaoran Jiang , Vincent Gripon , Claude Berrou , Michael Rabbat This is my paper

classification cs.NE

keywords efficiencyextensionhighintroducednetworksneuralredundancysequence

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An extension to a recently introduced architecture of clique-based neural networks is presented. This extension makes it possible to store sequences with high efficiency. To obtain this property, network connections are provided with orientation and with flexible redundancy carried by both spatial and temporal redundancy, a mechanism of anticipation being introduced in the model. In addition to the sequence storage with high efficiency, this new scheme also offers biological plausibility. In order to achieve accurate sequence retrieval, a double layered structure combining hetero-association and auto-association is also proposed.

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