Invention Grant
US09015096B2 Continuous time spiking neural network event-based simulation that schedules co-pending events using an indexable list of nodes 有权
使用可索引的节点列表来连续计时神经网络基于事件的模拟

  • Patent Title: Continuous time spiking neural network event-based simulation that schedules co-pending events using an indexable list of nodes
  • Patent Title (中): 使用可索引的节点列表来连续计时神经网络基于事件的模拟
  • Application No.: US13483876
    Application Date: 2012-05-30
  • Publication No.: US09015096B2
    Publication Date: 2015-04-21
  • Inventor: Jason Frank Hunzinger
  • Applicant: Jason Frank Hunzinger
  • Applicant Address: US CA San Diego
  • Assignee: QUALCOMM Incorporated
  • Current Assignee: QUALCOMM Incorporated
  • Current Assignee Address: US CA San Diego
  • Agent Rupit M. Patel
  • Main IPC: G06F17/00
  • IPC: G06F17/00 G06N3/02 G06N3/04
Continuous time spiking neural network event-based simulation that schedules co-pending events using an indexable list of nodes
Abstract:
Certain aspects of the present disclosure provide methods and apparatus for a continuous-time neural network event-based simulation that includes a multi-dimensional multi-schedule architecture with ordered and unordered schedules and accelerators to provide for faster event sorting; and a formulation of modeling event operations as anticipating (the future) and advancing (update/jump ahead/catch up) rules or methods to provide a continuous-time neural network model. In this manner, the advantages include faster simulation of spiking neural networks (order(s) of magnitude); and a method for describing and modeling continuous time neurons, synapses, and general neural network behaviors.
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