Storing Sequences in Binary Tournament-Based Neural Networks

IEEE Trans Neural Netw Learn Syst. 2016 May;27(5):913-25. doi: 10.1109/TNNLS.2015.2431319.

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 redundancies, 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 heteroassociation and autoassociation is also proposed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Computer Simulation
  • Models, Neurological*
  • Neural Networks, Computer*
  • Neurons*