Delay for the capacity-simplicity dilemma in associative memory attractor networks.

We consider the issue of how a simple network with delayed feedback can exhibit complex but desired dynamical behaviors for memory storage and retrieval. We discuss the simplicity-capacity dilemma arising from the requirement of both large capacity and easy implementation in additive networks. We then propose a novel approach based on signal processing delay and show that the interaction of delay, feedback and refractoriness in a simple inhibitory network of three neurons can generate mathematically trackable coexisting periodic patterns. Therefore, a simple and small network with delayed feedback can process a large amount of information, and time lag in our biological or artificial neural nets is useful for information processing. How the connection topology of a large network enhances the network's capacity for memory storage and retrieval remains to be an interesting task.

Multiple epidemic waves in delayed susceptible-infected-recovered models on complex networks.

We consider a delayed susceptible-infected-recovered epidemic model on an uncorrelated complex network and address the effect of time lag on the shape and multiple waves of epidemic curves. We show that when the transmission rate is above a threshold, a large delay can cause multiple waves with larger amplitudes in the second and subsequent waves.