DocumentCode
3382420
Title
A log-domain implementation of the Izhikevich neuron model
Author
Van Schaik, André ; Jin, Craig ; McEwan, Alistair ; Hamilton, Tara Julia
Author_Institution
Electr. & Inf. Eng., Univ. of Sydney, Sydney, NSW, Australia
fYear
2010
fDate
May 30 2010-June 2 2010
Firstpage
4253
Lastpage
4256
Abstract
We present an implementation of the Izhikevich neuron model which uses two first-order log-domain low-pass filters and two translinear multipliers. The neuron consists of a leaky-integrate-and-fire core, a slow adaptive state variable and quadratic positive feedback. Simulation results show that this neuron can emulate different spiking behaviours observed in biological neurons.
Keywords
low-pass filters; neural nets; Izhikevich neuron model; leaky-integrate-and-fire core; log-domain implementation; low-pass filters; quadratic positive feedback; slow adaptive state variable; translinear multipliers; Australia; Biological system modeling; Biomembranes; Circuit simulation; Computational efficiency; Computational modeling; Equations; Low pass filters; Mathematical model; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on
Conference_Location
Paris
Print_ISBN
978-1-4244-5308-5
Electronic_ISBN
978-1-4244-5309-2
Type
conf
DOI
10.1109/ISCAS.2010.5537564
Filename
5537564
Link To Document