The Super-Turing Computational Power of plastic Recurrent Neural Networks

@article{Cabessa2014TheSC,
  title={The Super-Turing Computational Power of plastic Recurrent Neural Networks},
  author={J{\'e}r{\'e}mie Cabessa and Hava T. Siegelmann},
  journal={International journal of neural systems},
  year={2014},
  volume={24 8},
  pages={1450029}
}
We study the computational capabilities of a biologically inspired neural model where the synaptic weights, the connectivity pattern, and the number of neurons can evolve over time rather than stay static. Our study focuses on the mere concept of plasticity of the model so that the nature of the updates is assumed to be not constrained. In this context, we show that the so-called plastic recurrent neural networks (RNNs) are capable of the precise super-Turing computational power--as the static… CONTINUE READING

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References

Publications referenced by this paper.
Showing 1-10 of 49 references

The Computer and the Brain (Yale University Press, New Haven, CT, USA, 1958). See Ref. 15 for the precise definition of ε-recognition

J. V. Neumann
The Super-Turing Computational Power of Plastic RNNs • 2014

Hypercomputation : Philosophical issues , Theor Alexandridis , Evolving RBF neural networks for adaptive soft - sensor design

S. Ghosh-Dastidar, H. Adeli
Int . J . Neural Syst . • 2013

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