Browse > Article
http://dx.doi.org/10.5573/JSTS.2015.15.6.658

Integrate-and-Fire Neuron Circuit and Synaptic Device using Floating Body MOSFET with Spike Timing-Dependent Plasticity  

Kwon, Min-Woo (Inter-university Semiconductor Research Center (ISRC) and Department of Electrical and Computer Engineering, Seoul National University)
Kim, Hyungjin (Inter-university Semiconductor Research Center (ISRC) and Department of Electrical and Computer Engineering, Seoul National University)
Park, Jungjin (Inter-university Semiconductor Research Center (ISRC) and Department of Electrical and Computer Engineering, Seoul National University)
Park, Byung-Gook (Inter-university Semiconductor Research Center (ISRC) and Department of Electrical and Computer Engineering, Seoul National University)
Publication Information
JSTS:Journal of Semiconductor Technology and Science / v.15, no.6, 2015 , pp. 658-663 More about this Journal
Abstract
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.
Keywords
Integrate-and-fire neuron circuit; synaptic transistor; spike-timing-dependent-plasticity; long and short-term memory; floating body MOSFET;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 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.
2 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.
3 H. Kim et al,. "Silicon-based floating-body synaptic transistor," International Conference on Solid State Devices and Materials, 2012, pp. 322-323.
4 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.
5 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.   DOI
6 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.   DOI
7 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.   DOI
8 R. Sarpeskar, L. Watts, and C. Mead, "Refractory neuron circuits," California Institute of Technology, CA, CNS Tech. Rep. 1992.
9 S H. Jo et al., "Nanoscale Memristor Device as Synapse in Neuromorphic Systems" Nano Letter, vol. 10, pp. 1297, 2010.   DOI
10 S. Park et al., "Nanoscale RRAM-based synaptic electronics: toward a neuromorphic computing device," nanotechnology, vol. 24, pp. 6, 2013.
11 K D. Cantley et al., Neural Networks, vol. 23, pp. 565, 2012.
12 D O. Hebb, The organization of behavior. A neuropsychological theory (New York: John Wiley and Sons),1949.