Suppressing chaos in neural networks by noise

Lutz Molgedey, Johannes Schuchhardt, Heinz Georg Schuster · Physical Review Letters · 1992

We study discrete parallel dynamics of a fully connected network of nonlinear elements interacting via long-range random asymmetric couplings under the influence of external noise. Using dynamical mean-field equations, which become exact in the thermodynamical limit, we calculate the activity and the maximal Lyapunov exponent of the network in dependence of a nonlinearity (gain) parameter and the noise intensity.

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