title: Leaky Integrate-and-Fire Neuron Circuit Based on Floating-Gate Integrator.
abstract: The artificial spiking neural network (SNN) is promising and has been brought to the notice of the theoretical neuroscience and neuromorphic engineering research communities. In this light, we propose a new type of artificial spiking neuron based on leaky integrate-and-fire (LIF) behavior. A distinctive feature of the proposed FG-LIF neuron is the use of a floating-gate (FG) integrator rather than a capacitor-based one. The relaxation time of the charge on the FG relies mainly on the tunnel barrier profile, e.g., barrier height and thickness (rather than the area). This opens up the possibility of large-scale integration of neurons. The circuit simulation results offered biologically plausible spiking activity (<100 Hz) with a capacitor of merely 6 fF, which is hosted in an FG metal-oxide-semiconductor field-effect transistor. The FG-LIF neuron also has the advantage of low operation power (<30 pW/spike). Finally, the proposed circuit was subject to possible types of noise, e.g., thermal noise and burst noise. The simulation results indicated remarkable distributional features of interspike intervals that are fitted to Gamma distribution functions, similar to biological neurons in the neocortex.
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and TechnologySeoul, South Korea; Department of Materials Science and Engineering, Seoul National University of Science and TechnologySeoul, South Korea.
authors.forename: Vladimir
authors.initials: V
authors.lastname: Kornijcuk
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and TechnologySeoul, South Korea; Department of Materials Science and Engineering, Seoul National UniversitySeoul, South Korea.
authors.forename: Hyungkwang
authors.initials: H
authors.lastname: Lim
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and TechnologySeoul, South Korea; Department of Materials Science and Engineering, Seoul National UniversitySeoul, South Korea.
authors.forename: Jun Yeong
authors.initials: JY
authors.lastname: Seok
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and TechnologySeoul, South Korea; Department of Materials Science and Engineering, Seoul National UniversitySeoul, South Korea.
authors.forename: Guhyun
authors.initials: G
authors.lastname: Kim
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and Technology Seoul, South Korea.
authors.forename: Seong Keun
authors.initials: SK
authors.lastname: Kim
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and Technology Seoul, South Korea.
authors.forename: Inho
authors.initials: I
authors.lastname: Kim
authors.affiliation: Department of Materials Science and Engineering, Seoul National University of Science and Technology Seoul, South Korea.
authors.forename: Byung Joon
authors.initials: BJ
authors.lastname: Choi
authors.affiliation: Center for Electronic Materials, Korea Institute of Science and Technology Seoul, South Korea.
authors.forename: Doo Seok
authors.initials: DS
authors.lastname: Jeong
keywords: floating-gate integrator; leaky integrate-and-fire neuron; spatial integration; spiking neural network; synaptic transistor