Communication information

Background

Shujun Liu is an associate professor in the Department of Microelectronics and Communication Engineering. She received the bachelor's degree in electrical engineering from the University of Xidian, in 2003. Her Ph.D degree in electrical engineering was received from Beihang University, in 2009.She is the expert reviewer of National Natural Science Foundation of China. Specially invited reviewer of international well-known SCI journals such as Digital signal processing, Information Sciences, etc. Herresearch interests include computer vision and signal processing. In recent years, she mainly engaged in machine learning, image processing, signal detection and estimation, sparse theory and application, remote sensing information and medical information processing. She has participated in more than 20 projects and published more than 40 academic papers.

Publications (papers)

(1) Jianxin Cao;Shujun Liu^*; Hongqing Liu; Hongwei Lu;CS-MRI reconstruction based on analysis dictionary learning and manifold structure regularization,Neural Networks,2020, 123: 0- 217–233.

(2) Cao, Jianxin; Liu, Shujun^*; Liu, Hongqing; Tan, Xiaoheng; Zhou, Xichuan;Sparse representation of classified patches for CS-MRI reconstruction ,Neurocomputing,2019, 339:255-269.

(3)Shujun Liu^*; Jianxin Cao; Hongqing Liu; Xiaoheng Tan; Xichuan Zhou;Group sparsity with orthogonal dictionary and nonconvex regularization for exact MRI reconstruction,Information Sciences, 2018, 451-452: 161-179.

(4)Shujun Liu^*; Jianxin Cao; Hongqing Liu; Xichuan Zhou; Kui Zhang;Zhengzhou Li;MRI reconstruction via enhanced group sparsity and nonconvex regularization,Neurocomputing, 2018, 272: 108-121.

(5)Shujun Liu^*; Jianxin Cao; Guoqing Wu; Hongqing Liu; Xiaoheng Tan;Xichuan Zhou;CS-MRI via reconstruction group-based eigenvalue decomposition and estimation,Neurocomputing, 2018, 283: 0-166–180.

(6)Ting Yang;Shujun Liu*;Hongqing Liu; Mingchun Tang; Xiaoheng Tan; Xichuan Zhou; Noise benefits

parameter estimation in LMMSE sense,Digital signal processing, 2018, 73: 153-163.

(7)Shujun Liu*; Guoqing Wu; Xinzheng Zhang; Kui Zhang; Pin Wang; Yongming Li; SAR despeckling via classification-based nonlocal and local sparse representation,Neurocomputing, 2017, 219: 174-185.

(8)Shujun Liu*; Jianxin Cao; Hongqing Liu; Xiaodong Shen; Kui Zhang; Pin Wang; MRI reconstruction using a joint constraint in patch-based total variational framework,Journal of Visual Communication & Image Representation, 2017, 46: 150-164.

(9)Shujun Liu*; Guoqing Wu; Hongqing Liu; Xinzheng Zhang; Image restoration approach using a joint sparse representation in 3D-transform domain,Digital signal processing, 2017, 60: 307-323.

(10)Shujun Liu*; Ting Yang; Kui Zhang; Noise enhancement for weighted sum of type I and II error probabilities with constraints,Entropy, 2017, 19: 1-22.

(11)Shujun Liu; Ting Yang; Hongqing Liu*; Optimal detection under the restricted Bayesian criterion,Entropy, 2017, 19: 1-18.

(12)Shujun Liu; Ting Yang; Mingchun Tang; Hongqing Liu*; Kui Zhang; Xinzheng Zhang; Optimal noise

benefit in composite hypothesis testing under different criteria,Entropy, 2016, 18: 1-18.

(13)Ting Yang;Shujun Liu*; Mingchun Tang; Kui Zhang; Xinzheng Zhang; Optimal noise enhanced signal

detection in a unified framework,Entropy,2016, 18: 1-21.

(14)Shujun Liu*; Ting Yang; Mingchun Tang; Pin Wang; Xinzheng Zhang; Suitable or optimal noise benefits in signal detection,Chaos Solitons & Fractals,2016, 85: 84-97.

(15)Shujun Liu*; Ting Yang; Xinzheng Zhang; Xiaoping Hu; Lipei Xu;Noise enhanced binary hypothesis- testing in a new framework,Digital Signal Processing,2015, 41: 22-31.