Potential Function Explain of the Quick Algorithm of Synergetic Neural Network
| dc.contributor.author | Bao, Jie | |
| dc.contributor.department | Department of Computer Science | |
| dc.date | 2018-02-13T23:49:42.000 | |
| dc.date.accessioned | 2020-06-30T01:56:00Z | |
| dc.date.available | 2020-06-30T01:56:00Z | |
| dc.date.issued | 2001-01-01 | |
| dc.description.abstract | <p>We can determine the winner pattern of the synergetic neural network directly from order parameters and attention parameters when the attention parameters are equal or constant. In this paper, we explain that the basis of that quick algorithm is that the potential function of network and attractive domain of each attractor are fully determined for given attention parameters, and there is an analytic approximation for the division of attractive domains.</p> | |
| dc.identifier | archive/lib.dr.iastate.edu/cs_techreports/232/ | |
| dc.identifier.articleid | 1236 | |
| dc.identifier.contextkey | 5462743 | |
| dc.identifier.s3bucket | isulib-bepress-aws-west | |
| dc.identifier.submissionpath | cs_techreports/232 | |
| dc.identifier.uri | https://dr.lib.iastate.edu/handle/20.500.12876/20053 | |
| dc.source.bitstream | archive/lib.dr.iastate.edu/cs_techreports/232/2001_06_24_potential_tr.pdf|||Fri Jan 14 22:47:44 UTC 2022 | |
| dc.subject.disciplines | Artificial Intelligence and Robotics | |
| dc.title | Potential Function Explain of the Quick Algorithm of Synergetic Neural Network | |
| dc.type | article | |
| dc.type.genre | article | |
| dspace.entity.type | Publication | |
| relation.isOrgUnitOfPublication | f7be4eb9-d1d0-4081-859b-b15cee251456 |
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