智林的科学之路分享 http://blog.sciencenet.cn/u/oliviazhang Sparse Signal Recovery, Bayesian Learning, Biomedical Signal Processing, Smart-Watch, Smart-Home, Health Monitoring

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2篇论文评为IEEE TBME期刊2013和2014最高引用论文(排名第1,第2)

已有 11374 次阅读 2014-11-1 15:16 |系统分类:论文交流

最近刚知道自己的2篇论文被评为2013至2014年发表在IEEE Trans. Biomedical Engineering上的最高引用论文,并且分别排名第一和第二 (http://tbme.embs.org/research-highlights/most-cited-articles/


这2篇论文分别是:

Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG via Block Sparse Bayesian Learning

Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao

IEEE Trans. on Biomedical Engineering, vol. 60, no. 2, pp. 300-309, 2013

[附注 : This paper used BSBL to reconstruct raw fetal ECG. It showed that BSBL can directly recover non-sparse correlated signals without using any dictionary matrix. It may be the first solid evidence showing that exploiting correlation is an effective way to reconstruct non-sparse signals in any domains.]


Compressed Sensing of EEG for Wireless Telemonitoring with Low Energy Consumption and Inexpensive Hardware

Zhilin Zhang, Tzyy-Ping Jung, Scott Makeig, Bhaskar D. Rao

IEEE Trans. on Biomedical Engineering, vol. 60, no. 1, pp. 221-224, 2013

[附注This paper applied BSBL to wireless telemonitoring of EEG, showing DCT coefficients can be recovered using block-structure model. Some explanations on why DCT dictionary matrix is a good dictionary for BSBL are further given in my ST-SBL paper.]






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