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ENGL
2008

A Solid-State Neuron for Spiking Neural Network Implementation

9 years 1 months ago
A Solid-State Neuron for Spiking Neural Network Implementation
This paper presents a compact analog neuron cell incorporating an array of charge-coupled synapses connected via a common output terminal. The novel silicon synapse is based on a two stage charge-coupled device where the weighting functionality can be integrated into the first stage. A presynaptic spike to the second gate allows the charge under the first gate to drift onto the floating diffusion output stage to produce a current, or voltage spike. Parallel defined synapses are each assigned to the left hand side of a current mirror gate where the right hand side feeds into a thresholding inverter. The decay of the membrane potential is mimicked by the charge leakage through a reverse-biased diode, whose model is verified by comparing the simulations and measured data. Spice simulation results show that the proposed neuron cell is capable of capturing the summing and thresholding dynamics of biological neurons.
Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2008
Where ENGL
Authors Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu, Peter M. Kelly
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