title: Stability of a neural network model with small-world connections.
abstract: Small-world networks are highly clustered networks with small distances among the nodes. There are many biological neural networks that present this kind of connection. There are no special weightings in the connections of most existing small-world network models. However, this kind of simply connected model cannot characterize biological neural networks, in which there are different weights in synaptic connections. In this paper, we present a neural network model with weighted small-world connections and further investigate the stability of this model.
authors.affiliation: Institute of Electronic Systems, College of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, 610054, People's Republic of China. cgli@uestc.edu.cn
authors.forename: Chunguang
authors.initials: C
authors.lastname: Li
authors.forename: Guanrong
authors.initials: G
authors.lastname: Chen
mesh_terms: D055592:Biophysical Phenomena; D001703:Biophysics; D015233:Models, Statistical; D008962:Models, Theoretical; D009415:Nerve Net