title: Phase dynamics of complex-valued neural networks and its application to traffic signal control.
abstract: Complex-valued Hopfield networks which possess the energy function are analyzed. The dynamics of the network with certain forms of an activation function is de-composable into the dynamics of the amplitude and phase of each neuron. Then the phase dynamics is described as a coupled system of phase oscillators with a pair-wise sinusoidal interaction. Therefore its phase synchronization mechanism is useful for the area-wide offset control of the traffic signals. The computer simulations show the effectiveness under the various traffic conditions.
authors.affiliation: College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan. nishi@ci.ritsumei.ac.jp
authors.forename: Ikuko
authors.initials: I
authors.lastname: Nishikawa
authors.forename: Takeshi
authors.initials: T
authors.lastname: Iritani
authors.forename: Kazutoshi
authors.initials: K
authors.lastname: Sakakibara
authors.forename: Yasuaki
authors.initials: Y
authors.lastname: Kuroe
mesh_terms: D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D003344:Cortical Synchronization; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*