Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Jiahe Shi"'
Autor:
Jingwen Jiang, Fengshi Tian, Jinhao Liang, Ziyang Shen, Yirui Liu, Jiapei Zheng, Hui Wu, Zhiyuan Zhang, Chaoming Fang, Yifan Zhao, Jiahe Shi, Xiaoyong Xue, Xiaoyang Zeng
Publikováno v:
Frontiers in Neuroscience, Vol 15 (2021)
In this work, a memristive spike-based computing in memory (CIM) system with adaptive neuron (MSPAN) is proposed to realize energy-efficient remote arrhythmia detection with high accuracy in edge devices by software and hardware co-design. A multi-la
Externí odkaz:
https://doaj.org/article/560c72884a054c9f9262bd9ddafd312b
Publikováno v:
IEEE Control Systems Letters. 7:229-234
This letter proposes a parallelizable algorithm for linear-quadratic model predictive control (MPC) problems with state and input constraints. The algorithm itself is based on a parallel MPC scheme that has originally been designed for systems with i
Autor:
Yizhuo Wang, Jiahe Shi, Hao Xu, Shujiang Ji, Yiyun Mao, Tenghao Zou, Jun Tao, Hao Min, Na Yan
Publikováno v:
IEEE Journal of Solid-State Circuits. :1-15
Publikováno v:
Medicine; 8/11/2023, Vol. 102 Issue 32, p1-4, 4p
Publikováno v:
Microelectronics Journal. 134:105696
Autor:
Boris Houska, Jiahe Shi
Publikováno v:
2022 American Control Conference (ACC).
Autor:
Fengshi Tian, Jingwen Jiang, Jinhao Liang, Zhiyuan Zhang, Jiahe Shi, Chaoming Fang, Hui Wu, Xiaoyong Xue, Xiaoyang Zeng
Publikováno v:
2022 IEEE International Symposium on Circuits and Systems (ISCAS).
Publikováno v:
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. :1-1
The ubiquity of edge devices has led to a growing amount of unlabeled data produced at the edge. Deep learning models deployed on edge devices are required to learn from these unlabeled data to continuously improve accuracy. Self-supervised represent
Publikováno v:
2021 IEEE/CVF International Conference on Computer Vision (ICCV).
Publikováno v:
TrustCom
Hardware Trojan is increasingly becoming a major threat in the filed of hardware security. To solve that security threat, we propose a novel strategy for hardware Trojan detection combining trustworthy design with thermal radiation analysis. We use r