Corpus ID: 12430344

Saturation Probabilities of Continuous-Time Sigmoidal Networks

  title={Saturation Probabilities of Continuous-Time Sigmoidal Networks},
  author={R. Beer and B. Daniels},
  journal={arXiv: Neurons and Cognition},
  • R. Beer, B. Daniels
  • Published 2010
  • Biology, Mathematics, Physics, Computer Science
  • arXiv: Neurons and Cognition
From genetic regulatory networks to nervous systems, the interactions between elements in biological networks often take a sigmoidal or S-shaped form. This paper develops a probabilistic characterization of the parameter space of continuous-time sigmoidal networks (CTSNs), a simple but dynamically-universal model of such interactions. We describe an efficient and accurate method for calculating the probability of observing effectively M-dimensional dynamics in an N-element CTSN, as well as a… Expand
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