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 Vol 9: An Attractor-Based Complexity Measurement for Boolean Recurrent Neural Networks.


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This article is from PLoS ONE, volume 9.AbstractWe 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 equivale

Author: Cabessa, Jeremie; Villa, Alessandro E. P.

Source: https://archive.org/







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