title: Itinerant memory dynamics and global bifurcations in chaotic neural networks.
abstract: We have considered itinerant memory dynamics in a chaotic neural network composed of four chaotic neurons with synaptic connections determined by two orthogonal stored patterns as a simple example of a chaotic itinerant phenomenon in dynamical associative memory. We have analyzed a mechanism of generating the itinerant memory dynamics with respect to intersection of a pair of alpha branches of periodic points and collapse of a periodic in-phase attracting set. The intersection of invariant sets is numerically verified by a novel method proposed in this paper.
authors.affiliation: Faculty of Engineering, Kagawa University, 2217-20 Hayashi, Takamatsu 761-0396, Japan.
authors.forename: Hiroyuki
authors.initials: H
authors.lastname: Kitajima
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Yoshinaga
authors.forename: Kazuyuki
authors.initials: K
authors.lastname: Aihara
authors.forename: Hiroshi
authors.initials: H
authors.lastname: Kawakami
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D015233:Models, Statistical; D008962:Models, Theoretical; D009415:Nerve Net; D016571:Neural Networks, Computer; D009474:Neurons / Q000378:metabolism; D017711:Nonlinear Dynamics