449 citations · 619 across the 51 of their papers we have counts for
6 papers · 1 filter
Nonconvex Nonsmooth Low-Rank Minimization for Generalized Image Compressed Sensing via Group Sparse Representation
Yunyi Li, Li Liu, Yu Zhao +2
Group sparse representation (GSR) based method has led to great successes in various image recovery tasks, which can be converted into a low-rank matrix minimization problem. As a…
From Group Sparse Coding to Rank Minimization: A Novel Denoising Model for Low-level Image Restoration
Yunyi Li, Guan Gui, Xiefeng Cheng
Recently, low-rank matrix recovery theory has been emerging as a significant progress for various image processing problems. Meanwhile, the group sparse coding (GSC) theory has led…
Deep Learning for Physical-Layer 5G Wireless Techniques: Opportunities, Challenges and Solutions
Hongji Huang, Song Guo, Guan Gui +4
The new demands for high-reliability and ultra-high capacity wireless communication have led to extensive research into 5G communications. However, the current communication system…
ADMM-IDNN: Iteratively Double-reweighted Nuclear Norm Algorithm for Group-prior based Nonconvex Compressed Sensing via ADMM
Yunyi Li, Fei Dai, Yu Zhao +2
Group-prior based regularization method has led to great successes in various image processing tasks, which can usually be considered as a low-rank matrix minimization problem. As…
Principal Component Analysis Based Broadband Hybrid Precoding for Millimeter-Wave Massive MIMO Systems
Yiwei Sun, Zhen Gao, Hua Wang +4
Hybrid analog-digital precoding is challenging for broadband millimeter-wave (mmWave) massive MIMO systems, since the analog precoder is frequency-flat but the mmWave channels are…
Deep-Learning-based Millimeter-Wave Massive MIMO for Hybrid Precoding
Hongji Huang, Yiwei Song, Jie Yang +2
Millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) has been regarded to be an emerging solution for the next generation of communications, in which hybrid analo…