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American Physical Society, Physical review E: Statistical, nonlinear, and soft matter physics, 3(72), 2005

DOI: 10.1103/physreve.72.031113

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System-size resonance in a binary attractor neural network

This paper is available in a repository.
This paper is available in a repository.

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Abstract

System size resonance (SSR) is a phenomenon in which the response of a system is optimal for a certain finite size, but poorer as the size goes to zero or infinity. In order to show SSR effects in binary attractor neural networks, we study the response of a network, in the ferromagnetic phase, to an external, time-dependent stimulus. Under the presence of such a stimulus, the network shows SSR, as is demonstrated by the measure of the signal amplification both analytically and by simulation.