Energy-Efficient High-Accuracy Spiking Neural Network Inference Using Time-Domain Neurons

Author:

Song Joonghyun1,Shirn Jiwon1,Kim Hanseok1,Choi Woo-Seok1

Affiliation:

1. Seoul National University,Department of ECE, ISRC,Seoul,South Korea

Funder

National Research Foundation of Korea

Publisher

IEEE

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Towards Chip-in-the-loop Spiking Neural Network Training via Metropolis-Hastings Sampling;2024 Neuro Inspired Computational Elements Conference (NICE);2024-04-23

2. A Subthreshold Time-Domain Analog Spiking Neuron With PLL-Based Leak Circuit and Capacitive DAC Synapse;IEEE Solid-State Circuits Letters;2024

3. An Analog Integrate-and-Fire Neuron with Robust Soft Reset Mechanism;2023 20th International SoC Design Conference (ISOCC);2023-10-25

4. 55 nm CMOS Mixed-Signal Neuromorphic Circuits for Constructing Energy-Efficient Reconfigurable SNNs;Electronics;2023-10-05

5. Validation of a CMOS SNN network based on a time-domain threshold neuron circuit achieving 114.90 pJ/inference on MNIST;2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS);2023-06-11

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