Storing sequences in binary tournament-based neural networks
Neural and Evolutionary Computing
2014-09-02 v1
Abstract
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.
Cite
@article{arxiv.1409.0334,
title = {Storing sequences in binary tournament-based neural networks},
author = {Xiaoran Jiang and Vincent Gripon and Claude Berrou and Michael Rabbat},
journal= {arXiv preprint arXiv:1409.0334},
year = {2014}
}