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Fractals in neurodynamics: From hybrid dynamical systems point of view
Authors:Kazutoshi?Gohara  author-information"  >  author-information__contact u-icon-before"  >  mailto:gohara@eng.hokudai.ac.jp"   title="  gohara@eng.hokudai.ac.jp"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author,Jun?Nishikawa
Affiliation:(1) Department of Applied Physics, Hokkaido University, 060-8628 Sapporo, Japan
Abstract:Recently, hybrid dynamical systems have attracted considerable attention in the automatic control domain. In this article, a theory for recurrent neural networks is presented from a hybrid dynamical systems point of view. The hybrid dynamical system is defined by a continuous dynamical system discretely switched by external temporal inputs. The theory suggests that the dynamics of continuous-time recurrent neural networks, which are stochastically excited by external temporal inputs, are generally characterized by a set of continuous trajectories with a fractal-like structure in hyper-cylindrical phase space. This work was presented, in part, at the 7th International Symposium on Artificial Life and Robotics, Oita, Japan, January 16–18, 2002
Keywords:Fractals  Hybrid dynamical systems  Recurrent neural networks
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