Bottom-Up and Top-Down Approaches for the Design of Neuromorphic Processing Systems: Tradeoffs and Synergies Between Natural and Artificial Intelligence-Reference-Cited by-同舟云学术

Bottom-Up and Top-Down Approaches for the Design of Neuromorphic Processing Systems: Tradeoffs and Synergies Between Natural and Artificial Intelligence

Published:2023-06 Issue:6 Volume:111 Page:623-652
ISSN:0018-9219
Container-title:Proceedings of the IEEE
language:
Short-container-title:Proc. IEEE

Author:

Frenkel Charlotte¹^ORCID,Bol David²^ORCID,Indiveri Giacomo¹^ORCID

Affiliation:

1. Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland

2. ICTEAM Institute, Université catholique de Louvain, Louvain-la-Neuve, Belgium

Funder

CHIST-ERA

European Research Council (ERC) through the European Union’s Horizon 2020 Research and Innovation Program

fonds européen de développement régional

Wallonia within the “Wallonie-2020.EU” Program

Plan Marshall

National Foundation for Scientific Research (F.R.S.-FNRS) of Belgium

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/5/10153467/10144567.pdf?arnumber=10144567

Reference353 articles.

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4. Spiking Neural Network Integrated Circuits: A Review of Trends and Future Directions

5. Point-to-point connectivity between neuromorphic chips using address events

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