Silicon Neuronal Network with Excitability Neurons for Edge Detection
- 10.2991/jimet-15.2015.128How to use a DOI?
- silicon neuronal network; digital spiking silicon neuron; silicon synapse; receptive field; edge detection
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.
- © 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/).
Cite this article
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 -