title: Chaotic pattern transitions in pulse neural networks.
abstract: In models of associative memory composed of pulse neurons, chaotic pattern transitions where the pattern retrieved by the network changes chaotically were found. The network is composed of multiple modules of pulse neurons, and when the inter-module connection strength decreased, the stability of pattern retrieval changed from stable to chaotic. It was found that the mixed pattern of stored patterns plays an important role in chaotic pattern transitions.
authors: Department of Innovative Mechanical Engineering, Faculty of Global Engineering, Kogakuin University, 139 Inume, Hachioji-city, Tokyo 193-0802, Japan. kanamaru@cc.kogakuin.ac.jp
authors: Takashi
authors: T
authors: Kanamaru
mesh_terms: D000465:Algorithms; D000818:Animals; D001244:Association; D002540:Cerebral Cortex / Q000502:physiology*; D003344:Cortical Synchronization; D006801:Humans; D008568:Memory / Q000502:physiology*; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009434:Neural Pathways; D009474:Neurons / Q000502:physiology*; D017711:Nonlinear Dynamics