Leaky-Integrate-and-Fire Neuron-Like Long-Short-Term-Memory Units as Model System in Computational Biology

Author:

Gerum Richard1ORCID,Erpenbeck André2,Krauss Patrick3,Schilling Achim3

Affiliation:

1. York University,Department of Physics and Astronomy,Toronto,Canada

2. University of Michigan,Department of Physics,Ann Arbor,United States

3. University Hospital Erlangen,Neuroscience Lab,Erlangen,Germany

Funder

Deutsche Forschungs-gemeinschaft (DFG, German Research Foundation)

Publisher

IEEE

Reference71 articles.

1. FitzHugh-Nagumo model

2. Long short-term memory and learning-to-learn in networks of spiking neurons;bellec;ArXiv Preprint,2018

3. A quantitative description of membrane current and its application to conduction and excitation in nerve

4. Hybrid Analog-Spiking Long Short-Term Memory for Energy Efficient Computing on Edge Devices

5. Liaf-net: Leaky integrate and analog fire network for lightweight and efficient spatiotem-poral information processing;wu;ArXiv Preprint,2020

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