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Abstract
We study a randomly diluted higher-order network of spinlike neurons that interact via Hebbian-type connections and derive and solve exact dynamical equations for a general block-sequential updating algorithm. The system has a variety of static and oscillatory solutions. The bifurcation parameters in the present model include neuronal interaction coefficients, the synchronicity parameter, and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise.
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