A 65-nm Neuromorphic Image Classification Processor With Energy-Efficient Training Through Direct Spike-Only Feedback-Reference-Cited by-同舟云学术

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A 65-nm Neuromorphic Image Classification Processor With Energy-Efficient Training Through Direct Spike-Only Feedback

Published:2020-01 Issue:1 Volume:55 Page:108-119
ISSN:0018-9200
Container-title:IEEE Journal of Solid-State Circuits
language:
Short-container-title:IEEE J. Solid-State Circuits

Author:

Park Jeongwoo,Lee Juyun,Jeon Dongsuk^ORCID

Funder

National Research Foundation of Korea

Korea Institute of Ocean Science and Technology

IC Design Education Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/4/8944135/08867974.pdf?arnumber=8867974

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2. ANP-I: A 28-nm 1.5-pJ/SOP Asynchronous Spiking Neural Network Processor Enabling Sub-0.1-μ J/Sample On-Chip Learning for Edge-AI Applications;IEEE Journal of Solid-State Circuits;2024-08

3. Two-Step Spike Encoding Scheme and Architecture for Highly Sparse Spiking-Neural-Network;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

4. Training an Ising machine with equilibrium propagation;Nature Communications;2024-04-30

5. Leveraging dendritic properties to advance machine learning and neuro-inspired computing;Current Opinion in Neurobiology;2024-04

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