System size resonance in an attractor neural network
We study the response of an attractor neural network, in the ferromagnetic phase, to an external, time-dependent stimulus, which drives the system periodically two different attractors. We demonstrate a non-trivial dependance of the system via a system size resonance, by showing a signal amplification maximum at a certain finite size.