arXiv · cond-mat/0512448
Bump formation in a binary attractor neural network
Abstract
This paper investigates the conditions for the formation of local bumps in the activity of binary attractor neural networks with spatially dependent connectivity. We show that these formations are observed when asymmetry between the activity during the retrieval and learning is imposed. Analytical approximation for the order parameters is derived. The corresponding phase diagram shows a relatively large and stable region, where this effect is observed, although the critical storage and the information capacities drastically decrease inside that region. We demonstrate that the stability of the network, when starting from the bump formation, is larger than the stability when starting even from the whole pattern. Finally, we show a very good agreement between the analytical results and the simulations performed for different topologies of the network.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Kostadin Koroutchev, Elka Korutcheva. 2005-12-19. Bump formation in a binary attractor neural network. https://doi.org/10.1103/physreve.73.026107
Cite the original work for its findings. Save a collection to share your selection of sources.