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Integrate-and-Fire Neuron Circuit and Synaptic Device using Floating Body MOSFET with Spike Timing-Dependent Plasticity
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 Title & Authors
Integrate-and-Fire Neuron Circuit and Synaptic Device using Floating Body MOSFET with Spike Timing-Dependent Plasticity
Kwon, Min-Woo; Kim, Hyungjin; Park, Jungjin; Park, Byung-Gook;
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In the previous work, we have proposed an integrate-and-fire neuron circuit and synaptic device based on the floating body MOSFET [1-3]. Integrate-and-Fire(I&F) neuron circuit emulates the biological neuron characteristics such as integration, threshold triggering, output generation, refractory period using floating body MOSFET. The synaptic device has short-term and long-term memory in a single silicon device. In this paper, we connect the neuron circuit and the synaptic device using current mirror circuit for summation of post synaptic pulses. We emulate spike-timing-dependent-plasticity (STDP) characteristics of the synapse using feedback voltage without controller or clock. Using memory device in the logic circuit, we can emulate biological synapse and neuron with a small number of devices.
Integrate-and-fire neuron circuit;synaptic transistor;spike-timing-dependent-plasticity;long and short-term memory;floating body MOSFET;
 Cited by
Bias Polarity Dependent Resistive Switching Behaviors in Silicon Nitride-Based Memory Cell, IEICE Transactions on Electronics, 2016, E99.C, 5, 547  crossref(new windwow)
M.-W. Kwon et al., "Integrate-and-fire neuron circuit and synaptic device with floating body MOSFETs," Journal of Semiconductor Technology and Science, pp. 755-759, 2014.

M.-W. Kwon et al., "Integrate-and-Fire neuron CMOS circuit with a multi-input floating body MOSFET," Silicon Nanoelectronics Workshop, 2013, pp. 113-114.

H. Kim et al,. "Silicon-based floating-body synaptic transistor," International Conference on Solid State Devices and Materials, 2012, pp. 322-323.

F. Tenore et al., " A programmable array of silicon neurons for the control of legged locomotion," in proc. IEEE Symp. Circuits and Systems, 2004, pp. 349-352.

D. H. Goldberg et al., "Probabilistic synaptic weighting in a reconfigurable network of VLSI integrate-and-fire neurons," IEEE Trans. Neural Netw., vol. 14, pp.781,2001. crossref(new window)

E. Chicca et al., "A VLSI recurrent network of integrate-and-fire neurons connected by plastic synapses with long term memory," IEEE Trans. Neural Netw., vol. 14, no. 5, pp.1297-1307, 2003. crossref(new window)

G. Indiveri et al., "A VLSI array of low-power spiking neurons and bistable synapses with spiketiming dependent plasticity," IEEE Trans. Neural Netw., vol. 17, no. 1, pp. 211-221, 2006. crossref(new window)

R. Sarpeskar, L. Watts, and C. Mead, "Refractory neuron circuits," California Institute of Technology, CA, CNS Tech. Rep. 1992.

S H. Jo et al., "Nanoscale Memristor Device as Synapse in Neuromorphic Systems" Nano Letter, vol. 10, pp. 1297, 2010. crossref(new window)

S. Park et al., "Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device," nanotechnology, vol. 24, pp. 6, 2013.

K D. Cantley et al., Neural Networks, vol. 23, pp. 565, 2012.

D O. Hebb, The organization of behavior. A neuropsychological theory (New York: John Wiley and Sons),1949.