DocumentCode
2957770
Title
A programmable facilitating synapse device
Author
Chen, Yajie ; McDaid, Liam ; Hall, Steve ; Kelly, Peter
Author_Institution
Dept. of Electr. Eng.&Electron., Univ. of Liverpool, Liverpool
fYear
2008
fDate
1-8 June 2008
Firstpage
1615
Lastpage
1620
Abstract
We present a programmable dynamic charge transfer synapse (CTS) in a single semiconductor device. The CTS comprises a metal oxide semiconductor (MOS) transistor operating in subthreshold and two MOS capacitors in proximity to the transistor. One of the capacitors is permanently biased in strong inversion where the associated density of charge in the well implements the weighting. When a presynaptic spike is applied to the gate of the second MOS capacitor the charge density in the well falls producing a current spike at the output. The amplitude of the spike is correlated with the equilibrium charge density in the well, which is controlled by the associated gate voltage. Aggregation of spikes from an array of CTSs is achieved by using a current mirror configuration whose output postsynaptic potential can be used to stimulate a point neuron circuit. The function of the MOS transistor is to restore the charge in the well where the duration of this process is dictated by the associated gate voltage. Therefore, the synapse is capability of operating in the facilitating state over a large frequency range. The CTS is compact and since it operates in transient mode, its power consumption is negligible. Simulation results are presented which clearly demonstrate its operation.
Keywords
MOS capacitors; MOSFET; neural chips; MOS capacitors; MOS transistor; equilibrium charge density; metal oxide semiconductor; mirror configuration; point neuron circuit; presynaptic spike; programmable dynamic charge transfer synapse; programmable facilitating synapse device; single semiconductor device; Charge transfer; Circuits; Energy consumption; Frequency; MOS capacitors; MOSFETs; Mirrors; Neurons; Semiconductor devices; Voltage control;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634013
Filename
4634013
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