Exponential pattern retrieval capacity with non-binary associative memory

  title={Exponential pattern retrieval capacity with non-binary associative memory},
  author={K. Raj Kumar and Amir Hesam Salavati and Amir H. Shokrollahi},
  journal={2011 IEEE Information Theory Workshop},
We consider the problem of neural association for a network of non-binary neurons. Here, the task is to recall a previously memorized pattern from its noisy version using a network of neurons whose states assume values from a finite number of non-negative integer levels. Prior works in this area consider storing a finite number of purely random patterns, and have shown that the pattern retrieval capacities (maximum number of patterns that can be memorized) scale only linearly with the number of… CONTINUE READING
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Introduction to the theory of neural computation

The advanced book program • 1991
View 4 Excerpts
Highly Influenced


C. Berrou
Gripon,Coded Hopfield Networks , Proc. Symp. on Turbo Codes and Iterative Information Processing, pp. 15 • 2010
View 2 Excerpts

Abbott,Theoretical neuroscience: computational and mathematical modeling of neural systems

L.F.P. Dayan
View 1 Excerpt

Improvements of complex-valued Hopfield associative memory by using generalized projection rules

D. L. Lee
IEEE Tran. Neur. Net.,Vol. 12, No. 2 • 2001
View 1 Excerpt

Miller,Expander graph arguments for message passing algorithms

G. D. Burshtein
IEEE Trans. Inform. Theory, • 2001
View 2 Excerpts

A Course in Computational Algebraic Number Theory

H. Cohen
Springer • 2000
View 1 Excerpt

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