Improving pattern reconstruction in neural networks by activity dynamics

I study the averaged dynamical behaviour of neural networks over an extended monitoring period, and consider pattern reconstruction procedures by activity clipping, selectively freezing, or sequentially freezing the dynamic nodes. They enable the retrieval precision to be improved, the basin of attraction to be widened, or the storage capacity to be increased, even when the information is not efficiently embedded in the synaptic weights.