Enlarged basin of attraction in neural networks with persistent stimuli
Andreas Engel, M. -C. Bouten, Andrzej Komoda, R. Serneels · Physical Review A · 1990
The basins of attraction of extremely diluted neural-network models in the presence of external neural stimuli parallel to the starting configuration are calculated analytically. For moderate values of the storage capacity \ensuremath{\alpha}, the basins of attraction can be enlarged significantly. For larger values of \ensuremath{\alpha}, the patterns are still locally stable but become dynamically blocked by the external stimuli so that the effective storage capacity decreases. The performance can be improved further by allowing for time-dependent stimuli.