An Energy-Efficient and Robust SNN Classifier for LC-ADC Sampled ECG Signals
Author:
Affiliation:
1. Fudan University,School of Information Science and Technology,Shanghai,China
2. Guangdong Institute of Intelligence Science and Technology,Large-scale Neuromorphic Computing Group,Guangdong,China
Funder
Research and Development
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10365709/10365561/10365892.pdf?arnumber=10365892
Reference14 articles.
1. Artificial intelligence-enhanced electrocardiography in cardiovascular disease management
2. Wearable Smart Textiles for Long-Term Electrocardiography Monitoring—A Review
3. An 82nW 0.53pJ/SOP Clock-Free Spiking Neural Network with 40µs Latency for AloT Wake-Up Functions Using Ultimate-Event-Driven Bionic Architecture and Computing-in-Memory Technique
4. An Ultra-Energy-Efficient and High Accuracy ECG Classification Processor With SNN Inference Assisted by On-Chip ANN Learning
5. A Neuromorphic Processing System With Spike-Driven SNN Processor for Wearable ECG Classification
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