Small World Neural Network Based on FPGA

DOI

10.2991/asei-15.2015.70How to use a DOI?

Keywords

Small World Network, Field Programmable Gate Array, Mirror Image Memory.

Abstract

Statistical analysis results have shown that small-world characteristics are widespread in the cerebral cortex neuron network, which has long been proven an effective method to investigate the brain anatomy and functions. From the perspective of hardware, we built the FHN neural network model with small-world connectivity using FPGA Field Programmable Gate Array . As a result, we observe the properties of neuron membrane potential are in line with the small-world characteristic of FHN neuron network model when impressed sinusoidal current with different frequencies. By the aforementioned rules, this paper demonstrates the effectiveness, and may underlie the construction of cerebral cortex network in the future.

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  - Aiqing Zhao
AU  - Huiyan Li
AU  - Yuliang Liu
AU  - Chunxiao Han
AU  - Yanqiu Che
PY  - 2015/05
DA  - 2015/05
TI  - Small World Neural Network Based on FPGA
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 326
EP  - 329
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.70
DO  - 10.2991/asei-15.2015.70
ID  - Zhao2015/05
ER  -