Poster Session (PSa-144～PSa-166)

[PSa-165] Finite-size effects and scaling laws in random neural networks: Emergence of chaos via torus-breakdown

*Hiromichi Suetani^1,2 (1. Oita Univeristy, 2. International Research Center for Neurointelligence(IRCN), The Univeersity of Tokyo)

キーワード：random neural networks, chaos, finite-size effect, Ruelle-Takens scenario, reservoir computing