Recall Time in Densely Encoded Hopfield Network: Results from KFS Theory and Computer Simulation

0404195 - UIVT-O 20010056 RIV AT eng C - Conference Paper (international conference)
Frolov, A. A. - Húsek, Dušan - Combe, P. - Snášel, V.
Recall Time in Densely Encoded Hopfield Network: Results from KFS Theory and Computer Simulation.
Artificial Neural Nets and Genetic Algorithms. Proceedings of the International conference. Wien: Springer, 2001 - (Kůrková, V.; Steele, N.; Neruda, R.; Kárný, M.), s. 74-77. ISBN 3-211-83651-9.
[ICANNGA'2001 /5./. Praha (CZ), 22.04.2001-25.04.2001]
R&D Projects: GA ČR GA201/01/1192; GA ČR GA201/00/1031
Grant - others:BARRANDE(XE) 99010-2
Institutional research plan: AV0Z1030915
Keywords : recall time * Hopfield networks * neural networks * parallel dynamics
Subject RIV: BB - Applied Statistics, Operational Research

Recall time in densely encoded Hopfield neural network with parallel dynamics is investigated analytically and by computer simulation. The method of the recall time estimation is based on calculation of overlaps between successive patterns of network dynamics. It is shown that this time actually gives rather accurate estimate for the recall time and that the overlap between successive patterns of network dynamics can be rather accurately estimated by the theory recently developed by Koyama et al.
Permanent Link: http://hdl.handle.net/11104/0124462