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All Projects → intel-nrc-ecosystem → models

intel-nrc-ecosystem / models

Licence: BSD-3-Clause license
This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform.

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spiking-neural-networksneuromorphic-computingloihi

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INRC Ecosystem

This repository will host models, modules, algorithms and applications developed by the INRC Community using nxsdk to run on the Intel Loihi Platform.

The repository is structured into directories. nxsdk_modules_ncl directory will be used to publish code/models which have been developed by maintainers of this repo. Researchers can publish and collaborate by publishing code/models within the nxsdk_modules_contrib directory. All code submissions will be reviewed. Please use the Github PR process. All contributed code will be distributed under the LICENSE provided with this repository.

To run the models, access to the Loihi software development kit (NxSDK) and the Loihi hardware is needed.

For more information, please visit: https://www.intel.com/content/www/us/en/research/neuromorphic-community.html For community support, Q&A and other information, please visit: http://neuromorphic.intel.com

Acknowledgments

  • Pelenet : Carlo Michaelis, University of Goettingen (https://github.com/sagacitysite/pelenet)

  • PCritical : Ismael Balafrej, prof. Jean Rouat. University of Sherbrooke. NEuro COmputational & Intelligent Signal Processing Research Group (NECOTIS)

  • Time Difference Encoder :

    • This is a Loihi implementation of the Time Difference Encoder (TDE) / spiking Elementary Motion Detector (sEMD). It converts a temporal difference between two spikes from different sources into a firing rate (number of spikes).

    • The TDE has been introduced and used by:

      • Milde, M. B., Bertrand, O. J., Ramachandran, H., Egelhaaf, M., & Chicca, E. (2018). Spiking elementary motion detector in neuromorphic systems. Neural computation, 30(9), 2384-2417.
      • D'Angelo, G., Janotte, E., Schoepe, T., O'Keeffe, J., Milde, M. B., Chicca, E., & Bartolozzi, C. (2020). Event-based eccentric motion detection exploiting time difference encoding. Frontiers in Neuroscience, 14, 451.

    • This file was started at the Telluride Neuromorphic Workshop 2019

    • Contributors:

    • Version 1.4

    • Updated for nxsdk version 1.0.0

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