Adaptive thresholds for layered neural networks with synaptic noise
| dc.creator | Bolle, D. | |
| dc.creator | Heylen, R. | |
| dc.date | 2006-05-24 | |
| dc.date.accessioned | 2026-07-07T07:09:09Z | |
| dc.date.available | 2026-07-07T07:09:09Z | |
| dc.description | The inclusion of a macroscopic adaptive threshold is studied for the retrieval dynamics of layered feedforward neural network models with synaptic noise. It is shown that if the threshold is chosen appropriately as a function of the cross-talk noise and of the activity of the stored patterns, adapting itself automatically in the course of the recall process, an autonomous functioning of the network is guaranteed.This self-control mechanism considerably improves the quality of retrieval, in particular the storage capacity, the basins of attraction and the mutual information content. | |
| dc.description | 10 pages, 5 figures, accepted for the ICANN 2006 conference | |
| dc.identifier | https://arxiv.org/abs/cond-mat/0605590 | |
| dc.identifier | http://arxiv.org/abs/cond-mat/0605590 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/110958 | |
| dc.subject | Disordered Systems and Neural Networks | |
| dc.subject | Statistical Mechanics | |
| dc.title | Adaptive thresholds for layered neural networks with synaptic noise | |
| dc.type | text |