Abstract:In this paper, we propose a novel source model for a magnetoencephalography (MEG) inverse problem that combines a conventional extended parametric approach and an imaging approach.Our aim is to separately identify a focal current source and background activities spread over the brain.The new source model consists of two terms to represent different spatial characteristics: one is a localized patch source represented with a few parameters based on a mapping from a sphere to the cortex surface,and the other is a distributed source expressed using elemental dipoles on grid points on the cortical surface. We call it a heterogeneous source model, because these two models have not been used simultaneously.Effectiveness of the proposed method is shown via numerical simulations.
Abstract:INPUT is a team participating in the RoboCup Soccer Small League (SSL). It aims to show the world the technological capabilities of the Nagaoka region of Niigata Prefecture, which is where the team members are from. For this purpose, we are working on one of the projects from the Nagaoka Activation Zone of Energy (NAZE). Herein, we introduce two robots, v2019 and v2022, as well as AI systems that will be used in RoboCup 2022. In addition, we describe our efforts to develop robots in collaboration with companies in the Nagaoka area.