白煌
一、导师基本情况
姓名：白煌，工学博士，副教授（硕士生导师）
邮箱：baihuang@hznu.edu.cn
指导专业：计算机应用技术，电子信息
二、研究领域
1. 信号建模
2. 数字图像处理
3. 稀疏表示与压缩感知
4. 矩阵分析与应用
5. 优化技术
6. 深度学习
三、主讲课程
1. 离散数学
2. Matlab程序设计
3. 数字图像处理
四、教育和工作经历
2006年9月--2010年6月，浙江工业大学，工学学士
2012年9月--2017年6月，浙江工业大学，工学博士
2017年10月至今，杭州师范大学信息科学与技术学院
五、学术简介
IEEE会员，杭州市高层次人才E类，主要研究方向为信号表示与建模、数字图像处理、矩阵分析、优化技术、深度学习等。发表相关论文50余篇，包括中科院二区以上SCI期刊论文10多篇。在ICASSP、DSP等国际知名会议上宣读文章10多次。主持1项国家自然科学基金项目，作为主要参与者参与4项国家自然科学基金项目、1项浙江省自然科学基金项目。指导或协助指导硕士研究生10多名、博士研究生2名。国际顶级期刊IEEE Transactions on Signal Processing、IEEE Transactions on Multimedia等审稿人。
六、主持教学科研项目（省部级以上）
1. 国家自然科学基金项目：基于不相干字典和确定型感知矩阵的鲁棒CS系统优化设计，61801159，主持
七、代表性论著
1. J. Hao#, H. Bai#, X. Li*, M. Panic, and J. Sun, “PLV-CSNet: Projected Landweber variant unfolding network for image compressive sensing reconstruction,” Neurocomputing, vol. 629, pp. 129723(1-12), May 2025.
2. X. Li, Z. Zhang, H. Bai*, L. Stanković, J. Hao, and J. Sun, “PIPO-Net: A penalty-based independent parameters optimization deep unfolding network,” Signal Processing, vol. 229, pp. 109796(1-7), Apr. 2025.
3. Z. Zhang#, H. Bai#, L. Stanković, J. Sun, and X. Li*, “A novel transmission-augmented deep unfolding network with consideration of residual recovery,” Complex & Intelligent Systems, vol. 11, no. 118, 1-15, Jan. 2025.
4. Q. Zhu, X. Li, J. Sun, and H. Bai*, “WDIG: A wavelet domain image generation framework based on frequency domain optimization,” EURASIP Journal on Advances in Signal Processing, vol. 66, no. 2023, pp. 1-22, Jun. 2023.
5. H. Bai, L. Stanković, and X. Li*, “Construction of unit norm tight frames inspired by the Paulsen problem,” Digital Signal Processing, Article ID 103590, May 2022.
6. H. Bai, C. Hong, S. Li, Y. D. Zhang, and X. Li*, “Unit-norm tight frame-based sparse representation with application to speech inpainting,” Digital Signal Processing, vol. 123, Article ID 103426, 19 pages, Apr. 2022.
7. H. Bai and X. Li*, “Measurement-driven framework with simultaneous sensing matrix and dictionary optimization for compressed sensing,” IEEE Access, vol. 8, no. 1, pp. 35950-35963, 2020.
8. X. Li*, H. Bai, and B. Hou, “A gradient-based approach to optimization of compressed sensing systems,” Signal Processing, vol. 139, pp. 49-61, Oct. 2017.
9. H. Bai, S. Li*, and X. He, “Sensing matrix optimization based on equiangular tight frames with consideration of sparse representation error,” IEEE Transactions on Multimedia, vol. 18, no. 10, pp. 2040-2053, Oct. 2016.
10. H. Bai, S. Li*, and Q. Jiang, “An efficient algorithm for learning dictionary under coherence constraint,” Mathematical Problems in Engineering, vol. 2016, Article ID 5737381, 11 pages, 2016.
11. G. Li*, X. Li, S. Li, H. Bai, Q. Jiang, and X. He, “Designing robust sensing matrix for image compression,” IEEE Transactions on Image Processing, vol. 24, no. 12, pp. 5389-5400, Dec. 2015.
12. H. Bai, G. Li*, S. Li, Q. Li, Q. Jiang, and L. Chang, “Alternating optimization of sensing matrix and sparsifying dictionary for compressed sensing,” IEEE Transactions on Signal Processing, vol. 63, no. 6, pp. 1581-1594, Mar. 2015.
13. G. Li*, Z. Zhu, D. Yang, L. Chang, and H. Bai, “On projection matrix optimization for compressive sensing systems,” IEEE Transactions on Signal Processing, vol. 61, no. 11, pp. 2887-2898, Jun. 2013.
14. Z. Zhang#, H. Bai#, L. Stanković, J. Sun, and X. Li*, “SuperTA-Net: A supervised transmission-augmented network for image compressive sensing reconstruction,” in 2024 6th International Conference on Data-driven Optimization of Complex Systems (DOCS 2024), pp. 586-593, Aug. 2024.
15. H. Bai, C. Hong, and X. Li*, “Construction of unit-norm tight frame based preconditioner for sparse coding,” in 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021), pp. 5400-5404, Jun. 2021.
16. J. Zhang, Y. Liu, Y. Wang, R. Zhu, Z. Liu, and H. Bai*, “Constructing preconditioner based on tight frame for Bernoulli random sensing matrix in compressed sensing,” in Proceedings of the 38th Chinese Control Conference (CCC 2019), pp. 3608-3612, Jul. 2019.
17. H. Bai* and X. Li, “Constructing equiangular tight frames based on singular values energy homogenization under normalization constraint,” in 2018 IEEE International Conference on Digital Signal Processing (DSP 2018), Nov. 2018.
18. H. Bai, S. Xu, S. Li*, R. C. de Lamare, X. He, and H. V. Poor, “Adaptive distributed compressed estimation based on recursive least squares with sensing matrix design,” in The 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016), pp. 3691-3695, Mar. 2016.
19. H. Bai*, X. Li, Q. Jiang, and S. Li, “On optimal sparsifying dictionary design with application to image inpainting,” in 2015 IEEE International Conference on Digital Signal Processing (DSP 2015), pp. 361-365, Jul. 2015.
20. H. Bai*, Z. Zhu, G. Li, and S. Li, “Design of optimal measurement matrix for compressive detection,” in The Tenth International Symposium on Wireless Communication Systems (ISWCS 2013), pp. 691-695, Aug. 2013.