BioPI: An Energy Efficient and Low-Latency Neuromorphic Pipelined System with Joint Design Optimizations of Sensor-Algorithm-Processor for Wearable Healthcare

Fengshi Tian, Jinbo Chen, Jiakun Zheng, Hui Wu, Jingyu He, Xiaomeng Wang, Chaoming Fang, Yao Yuan, Jie Yang, Mohamad Sawan, Chi-Ying Tsui et Kwang-Ting Cheng

Article de revue (2024)

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Mots clés

• Electrical and Electronic Engineering
• CCD and CMOS Imaging Sensors
• Advanced Memory and Neural Computing

Département:	Département de génie électrique
URL de PolyPublie:	https://publications.polymtl.ca/65433/
Titre de la revue:	IEEE transactions on circuits and systems for artificial intelligence.
DOI:	10.1109/tcasai.2024.3502573
URL officielle:	https://doi.org/10.1109/tcasai.2024.3502573
Date du dépôt:	07 mai 2025 15:34
Dernière modification:	07 mai 2025 15:34

Citer en APA 7:

Tian, F., Chen, J., Zheng, J., Wu, H., He, J., Wang, X., Fang, C., Yuan, Y., Yang, J., Sawan, M., Tsui, C.-Y., & Cheng, K.-T. (2024). BioPI: An Energy Efficient and Low-Latency Neuromorphic Pipelined System with Joint Design Optimizations of Sensor-Algorithm-Processor for Wearable Healthcare. IEEE transactions on circuits and systems for artificial intelligence., 1-17. https://doi.org/10.1109/tcasai.2024.3502573

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