Y
Yin Zhang
Researcher at University of Electronic Science and Technology of China
Publications - 322
Citations - 7094
Yin Zhang is an academic researcher from University of Electronic Science and Technology of China. The author has contributed to research in topics: Radar & Radar imaging. The author has an hindex of 35, co-authored 273 publications receiving 4960 citations. Previous affiliations of Yin Zhang include Huazhong University of Science and Technology & Nanjing University.
Papers
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Journal ArticleDOI
Design of QoS-Aware Multi-Level MAC-Layer for Wireless Body Area Network
TL;DR: The experimental results show that the proposed multi-level based QoS provisioning solution in WBAN yields better performance for meeting QoS requirements of personalized healthcare applications while achieving energy saving.
Journal ArticleDOI
Real-time transient stability status prediction using cost-sensitive extreme learning machine
TL;DR: A new RTSSP method based on cost-sensitive extreme learning machine (CELM) is proposed, which meets the demands for the computation speed and the reliability of R TSSP, and is implemented on the New England 39-bus electrical power system.
Journal ArticleDOI
Communication-Efficient Offloading for Mobile-Edge Computing in 5G Heterogeneous Networks
TL;DR: An ultralow-latency service deployment architecture in 5G heterogeneous networks is proposed, and three cognitive engines are the key components for efficient service communication across the terminal/edge/cloud computing structure.
Proceedings ArticleDOI
Doppler beam sharpening imaging based on fast iterative adaptive approach
TL;DR: In this paper, a Doppler beam sharpening (DBS) imaging method was proposed to achieve the high azimuth resolution in the forward-squint region based on fast iterative adaptive approach (F-IAA).
Proceedings ArticleDOI
TSVD with least squares optimization for scanning radar angular super-resolution
TL;DR: In this article, the angular super-resolution problem is converted into an inverse problem, which is described by a linear combination of a set of singular values, and the truncated singular value decomposition (TSVD) with the least squares optimization technique, termed as LSTSVD is developed.