MEMORY CAPACITY IN SYMMETRIC NEURAL NETWORKS: RIGOROUS BOUNDS.

Research output: Contribution to conferencePaperpeer-review

Abstract

Summary form only given. The author considers neural networks with N binary neurons and symmetric lth-order synaptic connections, in which m randomly chosen N-bit patterns are stored and retrieved with a small fraction delta of bit errors allowed. The analysis yields rigorous lower bounds for the maximum possible value of l factorial multiplied by alpha , the number of stored bits per distinct synapse: 0. 11 for l equals 2 (compared to 0. 29 as estimated by Hopfield and Amit et al. ), 0. 22 for l equals 3 and 0. 16 for l equals 4.

Original languageEnglish (US)
Number of pages1
StatePublished - 1987

ASJC Scopus subject areas

  • Engineering(all)

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