The effect of synchronized area on SOC behavior in a kind of Neural Network Model

Based on the LISSOM model and the OFC earthquake model, we introduce a self-organized feature map Neural Network model . It displays a “Self Organized Criticality”(SOC) behavior. It can be seen that the feature area (synchronized area) produced by self-organized process brings about some definite effect on SOC behavior and the system evolves into a “partly-synchronized” state. For explaining this phenomena, a quasi-OFC earthquake model is simulated.