NWNsim
This repository contains code to simulate neuromorphic nanowire networks and produce all simulations analysis for the manuscript
Joel Hochstetter, Ruomin Zhu, Alon Loeffler, Adrian Diaz-Alvarez, Tomonobu Nakayama, Zdenka Kuncic. Avalanches and edge-of-chaos learning in neuromorphic nanowire networks. Nature Communications 12, 4008 (2021). https://doi.org/10.1038/s41467-021-24260-z
Simulation and network generation code is written by past and present members of the Kuncic group at the University of Sydney: Joel Hochstetter, Ruomin Zhu, Alon Loeffler, Zdenka Kuncic, Paula Sanz-Leon, Ido Marcus and Miro Astore. Authors of each function are attributed within.
Please direct questions to Joel Hochstetter (joel.hochstetter@sydney.edu.au).
Requirements
For simulations MATLAB is required. Code has been tested on MATLAB2016b and MATLAB2020b.
The following MATLAB toolboxes are required:
- Signal Processing Toolbox
- Statistics and Machine Learning Toolbox
- Deep Learning Toolbox
For network generation: Python 2.7 or above is required. Two pre-generated networks are provided.
Getting started
Add all files and sub-folders in "simulator" to the MATLAB path. Follow instructions in "figures" folder to run the necessary simulations and analysis for each figure from the manuscript.
License
This code is for non-commercial use under a CC BY license (Creative Commons Attribution 4.0 International License).