Multistability in recurrent neural networks
| dc.citation.epage | 1320 | en_US |
| dc.citation.issue | 4 | en_US |
| dc.citation.spage | 1301 | en_US |
| dc.citation.volume | 66 | en_US |
| dc.citation.woscount | 69 | |
| dc.contributor.author | Cheng, CY | en_US |
| dc.contributor.author | Lin, KH | en_US |
| dc.contributor.author | Shih, CW | en_US |
| dc.contributor.department | 應用數學系 | zh_TW |
| dc.contributor.department | Department of Applied Mathematics | en_US |
| dc.date.accessioned | 2014-12-08T15:17:36Z | |
| dc.date.available | 2014-12-08T15:17:36Z | |
| dc.date.issued | 2006 | en_US |
| dc.description.abstract | Stable stationary solutions correspond to memory capacity in the application of associative memory for neural networks. In this presentation, existence of multiple stable stationary solutions for Hopfield-type neural networks with delay and without delay is investigated. Basins of attraction for these stationary solutions are also estimated. Such a scenario of dynamics is established through formulating parameter conditions based on a geometrical setting. The present theory is demonstrated by two numerical simulations on the Hopfield neural networks with delays. | en_US |
| dc.identifier.doi | 10.1137/050632440 | en_US |
| dc.identifier.issn | 0036-1399 | en_US |
| dc.identifier.journal | SIAM JOURNAL ON APPLIED MATHEMATICS | en_US |
| dc.identifier.uri | http://dx.doi.org/10.1137/050632440 | en_US |
| dc.identifier.uri | https://ir.lib.nycu.edu.tw/handle/11536/12771 | |
| dc.identifier.wosnumber | WOS:000238324300010 | |
| dc.language.iso | en_US | en_US |
| dc.subject | neural network | en_US |
| dc.subject | multistability | en_US |
| dc.subject | delay equations | en_US |
| dc.title | Multistability in recurrent neural networks | en_US |
| dc.type | Article | en_US |