Towards a more analytical training of neural networks and neuro-fuzzy systems
When used for function approximation purposes, neural networks belong to a class of models whose parameters can be separated into linear and nonlinear, according to their influence in the model output. In this work we extend this concept to the case where the training problem is formulated as the mi...
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| Outros Autores: | , |
| Formato: | conferenceObject |
| Idioma: | eng |
| Publicado em: |
2013
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/10400.1/2171 |
| País: | Portugal |
| Oai: | oai:sapientia.ualg.pt:10400.1/2171 |