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Parametric Learning of Associative Functional Networks Through a Modified Memetic Self-adaptive Firefly Algorithm
Functional networks are a powerful extension of neural networks where the scalar weights are replaced by neural functions. This paper concerns the problem of parametric learning of the associative model, a functional network that represents the associativity operator. This problem can be formulated...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302572/ http://dx.doi.org/10.1007/978-3-030-50426-7_42 |