Noise-Optimized Neuromorphic Spiking Radio in Context-Aware IoT
Editor’s notes: This article proposes a neuromorphic spiking radio using noise-optimized eNeurons to operate under stochastic resonance and transistors in weak inversion. –Ney Calazans, Federal University of Santa Catarina (UFSC), Brazil –Bruno Zatt, Federal University of Pelotas (UFPel), Brazil
Authors
- Pietro Maris Ferreira (ORCID: https://orcid.org/0000-0002-0038-9058)
- Zalfa Jouni (ORCID: https://orcid.org/0000-0002-6669-8005)
- Aziz Benlarbi‐Delaï (ORCID: https://orcid.org/0000-0003-4654-4735)
- G. Klisnick
- Siqi Wang (ORCID: https://orcid.org/0000-0001-7246-5235)
Institutions
- Centre National de la Recherche Scientifique (FR)
- CentraleSupélec (FR)
Publication Details
- Journal
- IEEE Design and Test
- Published
- 2025-03-04
- DOI
- https://doi.org/10.1109/mdat.2025.3547974
- Citations
- 1
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.73