Phase dynamics of complex-valued neural networks and its application to traffic signal control.
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.
Nishikawa
Ikuko
I
College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga 525-8577, Japan. nishi@ci.ritsumei.ac.jp
Iritani
Takeshi
T
Sakakibara
Kazutoshi
K
Kuroe
Yasuaki
Y
D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D003344:Cortical Synchronization; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*