NDLI: A Generalized Rotate-and-Fire Digital Spiking Neuron Model and Its On-FPGA Learning

Content Provider	IEEE Xplore Digital Library
Author	Matsubara, T. Torikai, H. Hishiki, T.
Copyright Year	2004
Abstract	A generalized rotate-and-fire digital spiking neuron model that can be implemented by a simple asynchronous sequential logic circuit is proposed. The model can exhibit various nonlinear phenomena and responses to stimulation inputs. It is shown that the model can reproduce five types of inhibitory responses of Izhikevich's simplified ordinary differential equation neuron model. In addition, field programmable gate array experiments show that a learning algorithm enables the model to automatically reproduce nonlinear responses of a biological neuron and neuron models in the neuron simulator.
Sponsorship	IEEE Circuits and Systems Society
Starting Page	677
Ending Page	681
Page Count	5
File Size	493793
File Format	PDF
ISSN	15497747
Volume Number	58
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Biological system modeling Integrated circuit modeling Heuristic algorithms Field programmable gate arrays Registers Biomembranes sequential logic circuit Cellular automaton (CA) field programmable gate array (FPGA) neuron model nonlinear dynamics on-chip learning
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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A Generalized Rotate-and-Fire Digital Spiking Neuron Model and Its On-FPGA Learning