A binary Hopfield network with $1/\log(n)$ information rate and applications to grid cell decoding

@inproceedings{Fiete2014ABH,
  title={A binary Hopfield network with \$1/\log(n)\$ information rate and applications to grid cell decoding},
  author={Ila Fiete and David J. Schwab and Ngoc Mai Tran},
  year={2014}
}
A Hopfield network is an auto-associative, distributive model of neural memory storage and retrieval. A form of error-correcting code, the Hopfield network can learn a set of patterns as stable points of the network dynamic, and retrieve them from noisy inputs – thus Hopfield networks are their own decoders. Unlike in coding theory, where the information rate of a good code (in the Shannon sense) is finite but the cost of decoding does not play a role in the rate, the information rate of… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 22 references

Error correcting analog codes in the brain: beyond classical population coding for exponentially precise computation

  • S Sreenivasan, I. Fiete
  • Nature Neuroscience
  • 2011
1 Excerpt

Residue Number Systems: Algorithms and Architectures. (Kluwer Academic Pub, Boston)

  • P. A. Mohan
  • 2002
1 Excerpt

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