A Ferroelectric Tunnel Junction-based Integrate-and-Fire Neuron
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
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.
Details
| Original language | English |
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| Title of host publication | 2022 29th IEEE International Conference on Electronics, Circuits and Systems (ICECS) |
| Place of Publication | Glasgow |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 1-4 |
| ISBN (electronic) | 9781665488235 |
| ISBN (print) | 978-1-6654-8824-2 |
| Publication status | Published - 2022 |
| Peer-reviewed | Yes |
Publication series
| Series | IEEE International Conference on Electronics, Circuits and Systems (ICECS) |
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Conference
| Title | 29th IEEE International Conference on Electronics, Circuits and Systems |
|---|---|
| Abbreviated title | ICECS 2022 |
| Conference number | 29 |
| Duration | 24 - 26 October 2022 |
| Website | |
| Location | University of Strathclyde |
| City | Glasgow |
| Country | United Kingdom |
External IDs
| dblp | conf/icecsys/GibertiniFLDMDS22 |
|---|---|
| ORCID | /0000-0003-3814-0378/work/142256250 |
Keywords
ASJC Scopus subject areas
Keywords
- edge computing, FTJ, HZO, Integrate-and-Fire Neuron, neuromorphic computing