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 :
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