title: Stability analysis and synchronization in discrete-time complex networks with delayed coupling.
abstract: A new network of coupled maps is proposed in which the connections between units involve no delays but the intra-neural communication does, whereas in the work of Atay et al. [Phys. Rev. Lett. 92, 144101 (2004)], the focus is on information processing delayed by the inter-neural communication. We show that the synchronization of the network depends on not only the intrinsic dynamical features and inter-connection topology (characterized by the spectrum of the graph Laplacian) but also the delays and the coupling strength. There are two main findings: (i) the more neighbours, the easier to be synchronized; (ii) odd delays are easier to be synchronized than even ones. In addition, compared with those discussed by Atay et al. [Phys. Rev. Lett. 92, 144101 (2004)], our model has a better synchronizability for regular networks and small-world variants.
authors.affiliation: Department of Mathematics, Beijing Jiao Tong University, Beijing 100 044, China.
authors.forename: Ranran
authors.initials: R
authors.lastname: Cheng
authors.affiliation: Department of Mathematics, Beijing Jiao Tong University, Beijing 100 044, China.
authors.forename: Mingshu
authors.initials: M
authors.lastname: Peng
authors.affiliation: Department of Mathematics, Beijing Jiao Tong University, Beijing 100 044, China.
authors.forename: Weibin
authors.initials: W
authors.lastname: Yu
authors.affiliation: School of Applied Mathematics, Central University of Finance and Economics, Beijing 100081, China.
authors.forename: Bo
authors.initials: B
authors.lastname: Sun
authors.affiliation: Department of Mathematics, Beijing Jiao Tong University, Beijing 100 044, China.
authors.forename: Jinchen
authors.initials: J
authors.lastname: Yu
mesh_terms: D000818:Animals; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*