Associative memory networks, fault-tolerance and coding theory

The binary-couplings neural network used as an associative memory is studied under the effects of synaptic damage. The model of damage is to flip synapses (J/sub ij/ to -J/sub ij/) randomly with a probability lambda . A simple model based on a network with constant stabilities is proposed that allows the calculation of the storage properties of the damaged networks. The networks are fault-tolerant at low storage densities, the fraction of bit-errors in the stored patterns being finite but very small up to high concentrations of flipped synapses. Results are compared with some standard error-correcting codes, some implications for coding-theory are discussed.<
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