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An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks
We provide a novel refined attractor-based complexity measurement for Boolean recurrent neural networks that represents an assessment of their computational power in terms of the significance of their attractor dynamics. This complexity measurement is achieved by first proving a computational equiva...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3984152/ https://www.ncbi.nlm.nih.gov/pubmed/24727866 http://dx.doi.org/10.1371/journal.pone.0094204 |