Silicon Neuronal Network with Excitability Neurons for Edge Detection

DOI

10.2991/jimet-15.2015.128How to use a DOI?

Keywords

silicon neuronal network; digital spiking silicon neuron; silicon synapse; receptive field; edge detection

Abstract

Inspired by the human vision system, neuromorphic vision systems simulating the mechanism of signal processing in retina are extensively investigated. This paper describes a silicon neuronal network with bio-inspired structure detects the edge information in image. The digital spiking silicon neuron (DSSN) and silicon synapse models are used to reproduce the neuron, synapse and their dynamic behaviors. The biological receptive fields are realized by the combination of excitatory and inhibitory synapses. Our silicon neuronal network is optimized for the hardware implementation. It is expected to have low hardware consumption and high running speed. The simulation results show that edge detection is successful in our network.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - J. Li
AU  - B. Liu
PY  - 2015/12
DA  - 2015/12
TI  - Silicon Neuronal Network with Excitability Neurons for Edge Detection
BT  - Proceedings of the 2015 Joint International Mechanical, Electronic and Information Technology Conference
PB  - Atlantis Press
SP  - 686
EP  - 692
SN  - 2352-538X
UR  - https://doi.org/10.2991/jimet-15.2015.128
DO  - 10.2991/jimet-15.2015.128
ID  - Li2015/12
ER  -