柏业超

通信工程系 博导

个人简历

2005.6,南京大学电子信息科学与技术专业毕业,获学士学位;
2010.6,南京大学信号与信息处理专业毕业,获博士学位;
2010.8至今,南京大学电子科学与工程学院任教;
2013.8-2014.8,密歇根大学安娜堡分校,访问学者。

研究方向

信号检测与估计、阵列信号处理、信息几何、随机矩阵理论

主要课程

电路分析、信号检测与估计

代表成果
  • Y. Yan, G. Wu, Y. Dong and Y. Bai, An Improved MSR-Based Data-Driven Detection Method Using Smoothing Pre-Processing, IEEE Signal Processing Letters, vol. 28, pp. 444-448, 2021.

  • J. Li, Y. Bai, Y. Zhang, F. Qu, Y. Wei and J. Wang, Cross Power Spectral Density Based Beamforming for Underwater Acoustic Communications, Ocean Engineering, vol. 216, 2020.

  • Y. Gao, J. Li, Y. Bai, Q. Wang and X. Zhang. An Improved Subspace Weighting Method Using Random Matrix Theory, Frontiers of Information Technology & Electronic Engineering, vol. 21, no. 9, pp. 1302–1307, 2020.

  • Z. Qi, Y. Bai, Q. Wang, X. Zhang and H. Chen, Optimal synthesis of reconfigurable sparse arrays via multi-convex programming, IET Radar, Sonar & Navigation, vol. 14, no. 8, pp. 1125-1134, 2020.

  • Y. Bai, Q. Wang, C. Lo, M. Liu, J. P. Lynch and X. Zhang, Adaptive Bayesian Group Testing: Algorithms and Performance, Signal Processing, vol. 156, pp. 191-207, 2019.

  • Y. Bai, J. Li, Y. Wu, Q. Wang and X. Zhang, Weighted Incoherent Signal Subspace Method for DOA Estimation on Wideband Colored Signals, IEEE Access, vol. 7, pp. 1224-1233, 2019.

  • H. Chen, X. Zhang, Q. Wang and Y. Bai, Efficient Data Fusion Using Random Matrix Theory, IEEE Signal Processing Letters, vol. 25, no. 5, pp. 605-609, 2018.

  • H. Chen, Y. Wei, Y. Bai and X. Zhang, Sparse Recovery for DOA Estimation With a Reflection Path, IEEE Access, vol. 6, pp. 70572-70581, 2018.


联系方式
电话:
邮件:ychbai@nju.edu.cn
信箱:
办公地址:南京大学仙林校区电子楼548

联系我们

  • TEL:025-8968 0678

    E-MAIL:jhmin@nju.edu.cn

    ADDRESS: Electronic Building 

    (Panzhonglai Building), 163 Xianlin Ave., Qixia District, Nanjing, Jiangsu Province, 210023