Combining lateral and elastic interactions: Topology-preserving elastic nets
We have developed a topology-preserving elastic net which combines both lateral and synaptic interactions to obtain topologically ordered representations (receptive fields) of an external stimulus. Existing neural models that preserve the topology by utilizing lateral interactions, such as the Kohon...
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| Veröffentlicht in: | Neural processing letters 2002-06, Vol.15 (3), p.213-223 |
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| container_title | Neural processing letters |
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| creator | TERESHKO, Valery ALLINSON, Nigel M |
| description | We have developed a topology-preserving elastic net which combines both lateral and synaptic interactions to obtain topologically ordered representations (receptive fields) of an external stimulus. Existing neural models that preserve the topology by utilizing lateral interactions, such as the Kohonen-type maps, and by utilizing synaptic interactions, such as elastic-type nets, appear as limiting cases of this model. Utilizing both lateral and synaptic interactions can be beneficial for preservation of the topology. |
| doi_str_mv | 10.1023/A:1015721115089 |
| format | Article |
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| ispartof | Neural processing letters, 2002-06, Vol.15 (3), p.213-223 |
| issn | 1370-4621 1573-773X |
| language | eng |
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| source | Springer Nature - Complete Springer Journals; ProQuest Central UK/Ireland; ProQuest Central |
| subjects | Applied sciences Artificial intelligence Computer science control theory systems Connectionism. Neural networks Elastic limit Exact sciences and technology Topology |
| title | Combining lateral and elastic interactions: Topology-preserving elastic nets |
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