Dynamics of neural networks with nonmonotonic neurons and adapting
synapses
Sebastiano Stramaglia
Abstract
We study a strongly diluted neural network with nonmonotonic neurons and
adapting synapses, whose dynamics can be analitically calculated.
Dynamics reduction is observed for low connectivity: the network has no
chaotic attractors in the stationary regime. For high connectivity chaos
is not completely removed. We present some evidence that the dynamics
reduction occurs, in the high connectivity case, when the synaptic
correlations become relevant.
Elenco dei partecipanti al convegno di Bari.