A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2022
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| _version_ | 1866909097016688640 |
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| author | Gibertini, Paolo Fehlings, Luca Lancaster, Suzanne Duong, Quang Mikolajick, Thomas Dubourdieu, Catherine Slesazeck, Stefan Covi, Erika Deshpande, Veeresh |
| author_facet | Gibertini, Paolo Fehlings, Luca Lancaster, Suzanne Duong, Quang Mikolajick, Thomas Dubourdieu, Catherine Slesazeck, Stefan Covi, Erika Deshpande, Veeresh |
| contents | Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory devices and are well-suited to be integrated in these systems. Here, we present a hybrid FTJ-CMOS Integrate-and-Fire neuron which constitutes a fundamental building block for new-generation neuromorphic networks for edge computing. We demonstrate electrically tunable neural dynamics achievable by tuning the switching of the FTJ device. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2211_02598 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron Gibertini, Paolo Fehlings, Luca Lancaster, Suzanne Duong, Quang Mikolajick, Thomas Dubourdieu, Catherine Slesazeck, Stefan Covi, Erika Deshpande, Veeresh Emerging Technologies Neural and Evolutionary Computing Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory devices and are well-suited to be integrated in these systems. Here, we present a hybrid FTJ-CMOS Integrate-and-Fire neuron which constitutes a fundamental building block for new-generation neuromorphic networks for edge computing. We demonstrate electrically tunable neural dynamics achievable by tuning the switching of the FTJ device. |
| title | A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron |
| topic | Emerging Technologies Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2211.02598 |