Abstract
We derive an analytic evolution equation for overlap parameters, including the effect of degree distribution on the transient dynamics of sequence processing neural networks. In the special case of globally coupled networks, the precisely retrieved critical loading ratio alpha_{c}=N;{-12} is obtained, where N is the network size. In the presence of random networks, our theoretical predictions agree quantitatively with the numerical experiments for delta, binomial, and power-law degree distributions.
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