title: Delay for the capacity-simplicity dilemma in associative memory attractor networks.
abstract: 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.
authors.affiliation: College of Mathematics and Econometrics, Hunan University, Changsha, Hunan 410082, China. shaofenzou@163.com
authors.forename: Shaofen
authors.initials: S
authors.lastname: Zou
authors.forename: Yuming
authors.initials: Y
authors.lastname: Chen
authors.forename: Jianfu
authors.initials: J
authors.lastname: Ma
authors.forename: Jianhong
authors.initials: J
authors.lastname: Wu
mesh_terms: D001245:Association Learning; D005246:Feedback; D009433:Neural Inhibition; D016571:Neural Networks, Computer; D055366:Synaptic Potentials; D013997:Time Factors