ABSTRACT
The present paper proposes an adaptive control law for inducing in-phase and antiphase synchronization in a pair of relaxation oscillators. We analytically show that the phase dynamics of the oscillators coupled by the control law is equivalent to that of Kuramoto phase oscillators and then extend the results for a pair of oscillators to three or more oscillators. We also provide a systematic procedure for designing the controller parameters for oscillator networks with all-to-all and ring topologies. Our numerical simulations demonstrate that these analytical results can be used to solve a dispatching problem encountered by automated guided vehicles (AGVs) in factories. AGV congestion can be avoided and the peak value of the amount of materials or parts in buffers can be suppressed.
ABSTRACT
This paper proposes a biologically plausible matching method to recognize general shapes based on contour curvature information. The human visual system recognizes general shapes flexibly in real-world scenes through the ventral pathway. The pathway is typically modeled using artificial neural networks. These network models, however, do not construct a shape representation that satisfies the following required constraints: (1) The original shape should be represented by a group of partitioned contours in order to retrieve the whole shape (global information) from the partial contours (local information). (2) Coarse and fine structures of the original shapes should be individually represented in order for the visual system to respond to shapes as quickly as possible based on the least number of their features, and to discriminate between shapes based on detailed information. (3) The shape recognition realized with an artificial visual system should be invariant to geometric transformation such as expansion, rotation, or shear. In this paper, we propose a visual shape representation with geometrically characterized contour partitions described on multiple spatial scales.