王超

个人信息Personal Information

研究员(自然科学)   博士生导师   硕士生导师  

性别:男

在职信息:在职

所在单位:光学与电子信息学院

学历:研究生(博士)毕业

学位:工学博士学位

毕业院校:南洋理工大学

学科:微电子学与固体电子学
电路与系统

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Near-Threshold Energy and Area Efficient Reconfigurable DWPT/DWT Processor for Healthcare Monitoring Applications

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论文类型:期刊论文

合写作者:C. Wang, J. Zhou, L. Liao, J. Lan, J. Luo, X. Liu,M. Je

发表刊物:IEEE Trans. on Circuits and Systems-II Express Briefs (TCAS-II) 2015

收录刊物:SCI

卷号:62

期号:1

页面范围:70-74

DOI码:10.1109/TCSII.2014.2362791

发表时间:2014-10-14

摘要:This brief presents an energy- and area-efficient discrete wavelet packet transform (DWPT) processor design for power-constrained and cost-sensitive healthcare-monitoring applications. This DWPT processor employs recursive memory-shared architecture to achieve low hardware complexity while performing required arbitrary-basis DWPT decomposition. By exploiting inherent characteristics of different physiological signals through an entropy statistic engine, the DWPT processor core can be reconfigured to compute multilevel wavelet decomposition with effective time and frequency resolution. Various design techniques from algorithm to circuit levels, including reconfigurable computing, lifting scheme, dual-port pipeline processing, near-threshold operation, and clock gating, are applied to achieve energy efficiency. With a 0.18- μm CMOS technology at 0.5 V and 1 MHz, the DWPT core only consumes 26 μW for performing three-level 256-point DWPT decomposition with entropy statistic calculation. When integrated in an ARM Cortex-M0-based biomedical system-on-a-chip test platform, the DWPT processor achieves processing acceleration by three orders of magnitude and reduces energy consumption by four orders of magnitude compared with CPU-only implementations.

发布期刊链接:https://ieeexplore.ieee.org/document/6922525