On-Chip Learning with a 15-neuron Digital Oscillatory Neural Network Implemented on ZYNQ Processor-Reference-Cited by-同舟云学术

On-Chip Learning with a 15-neuron Digital Oscillatory Neural Network Implemented on ZYNQ Processor

Published:2022-07-27 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the International Conference on Neuromorphic Systems 2022
language:
Short-container-title:

Author:

Abernot Madeleine¹,Gil Thierry¹,Todri-Sanial Aida¹

Affiliation:

1. LIRMM, University of Montpellier, CNRS, France

Funder

European H2020 Programme NeurONN

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3546790.3546822

Reference15 articles.

1. Digital Implementation of Oscillatory Neural Network for Image Recognition Applications

2. Dennis Valbjørn Christensen and al. 2022. 2022 roadmap on neuromorphic computing and engineering. Neuromorphic Computing and Engineering(2022). http://iopscience.iop.org/article/10.1088/2634-4386/ac4a83 Dennis Valbjørn Christensen and al. 2022. 2022 roadmap on neuromorphic computing and engineering. Neuromorphic Computing and Engineering(2022). http://iopscience.iop.org/article/10.1088/2634-4386/ac4a83

3. Digilent company. [n.d.]. Zybo Z7 Reference Manual. ([n. d.]). https://digilent.com/reference/programmable-logic/zybo-z7/reference-manual Digilent company. [n.d.]. Zybo Z7 Reference Manual. ([n. d.]). https://digilent.com/reference/programmable-logic/zybo-z7/reference-manual

4. Gyorgy Csaba and Wolfgang Porod . 2020. Coupled oscillators for computing: A review and perspective. Applied physics reviews 7 ( 2020 ), 011302. Gyorgy Csaba and Wolfgang Porod. 2020. Coupled oscillators for computing: A review and perspective. Applied physics reviews 7 (2020), 011302.

5. Mapping Hebbian Learning Rules to Coupling Resistances for Oscillatory Neural Networks

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