Inspired by neurobiological systems, Spiking Neural Networks (SNNs) are gaining an increasing interest in the field of bio-inspired machine learning. Neurons, as central processing and short-term memory units of biological neural systems, are thus at the forefront of cutting-edge research approaches. The realization of CMOS circuits replicating neuronal features, namely the integration of action potentials and firing according to the all-or-nothing law, imposes various challenges like large area and power consumption. The non-volatile storage of polarization states and accumulative switching behavior of nanoscale HfO₂ - based Ferroelectric Field-Effect Transistors (FeFETs), promise to circumvent these issues. In this paper, we propose two FeFET-based neuronal circuits emulating the Integrate-and-Fire (I&F) behavior of biological neurons on the basis of SPICE simulations. Additionally, modulating the depolarization of the FeFETs enables the replication of a biology-based concept known as membrane leakage. The presented capacitor-free implementation is crucial for the development of neuromorphic systems that allow more complex features at a given area and power constraint.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:77196 |
| Date | 03 January 2022 |
| Creators | Suresh, Bharathwaj, Bertele, Martin, Breyer, Evelyn T., Klein, Philipp, Mulaosmanovic, Halid, Mikolajick, Thomas, Slesazeck, Stefan, Chicca, Elisabetta |
| Publisher | IEEE |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 978-1-7281-0996-1, 10.1109/ICECS46596.2019.8965004, info:eu-repo/grantAgreement/Deutsche Forschungsgemeinschaft/Cluster of Excellence at Bielefeld University/EXC 277//Cognitive Interaction Technology /CITEC |
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