Self-control dynamics for sparsely coded networks with synaptic noise
| dc.creator | Bolle', D. | |
| dc.creator | Heylen, R. | |
| dc.date | 2004-03-23 | |
| dc.date.accessioned | 2026-07-07T02:57:13Z | |
| dc.date.available | 2026-07-07T02:57:13Z | |
| dc.description | For the retrieval dynamics of sparsely coded attractor associative memory models with synaptic noise the inclusion of a macroscopic time-dependent threshold is studied. It is shown that if the threshold is chosen appropriately as a function of the cross-talk noise and of the activity of the memorized patterns, adapting itself automatically in the course of the time evolution, an autonomous functioning of the model is guaranteed. This self-control mechanism considerably improves the quality of the fixed-point retrieval dynamics, in particular the storage capacity, the basins of attraction and the mutual information content. | |
| dc.description | 5 pages Latex, 1 ps and 4 eps figures, to appear in the proceedings of the 2004 International Joint Conference on Neural Networks, Budapest (IEEE) | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0403576 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0403576 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/23579 | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.subject | Statistical Mechanics | |
| dc.title | Self-control dynamics for sparsely coded networks with synaptic noise | |
| dc.type | text |