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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...

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Detalhes bibliográficos
Main Authors: Cabessa, Jérémie, Villa, Alessandro E. P.
Formato: Artigo
Idioma:Inglês
Publicado em: Public Library of Science 2014
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC3984152/
https://ncbi.nlm.nih.gov/pubmed/24727866
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0094204
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