58 citations · 64 across the 5 of their papers we have counts for
7 papers
Cross-Validated Tuning of Shrinkage Factors for MVDR Beamforming Based on Regularized Covariance Matrix Estimation
Lei Xie, Zishu He, Jun Tong +2
This paper considers the regularized estimation of covariance matrices (CM) of high-dimensional (compound) Gaussian data for minimum variance distortionless response (MVDR) beamfor…
On the Performance of Massive MIMO Systems With Low-Resolution ADCs Over Rician Fading Channels
Tianle Liu, Jun Tong, Qinghua Guo +3
This paper considers uplink massive multiple-input multiple-output (MIMO) systems with lowresolution analog-to-digital converters (ADCs) over Rician fading channels. Maximum-ratio-…
Channel Covariance Matrix Estimation via Dimension Reduction for Hybrid MIMO MmWave Communication Systems
Rui Hu, Jun Tong, Jiangtao Xi +2
Hybrid massive MIMO structures with lower hardware complexity and power consumption have been considered as a potential candidate for millimeter wave (mmWave) communications. Chann…
Extreme Learning Machine Based Non-Iterative and Iterative Nonlinearity Mitigation for LED Communications
Dawei Gao, Qinghua Guo, Jun Tong +3
This work concerns receiver design for light emitting diode (LED) communications where the LED nonlinearity can severely degrade the performance of communications. We propose extre…
Linear Shrinkage Estimation of Covariance Matrices Using Low-Complexity Cross-Validation
Jun Tong, Rui Hu, Jiangtao Xi +3
Shrinkage can effectively improve the condition number and accuracy of covariance matrix estimation, especially for low-sample-support applications with the number of training samp…
Defect detection for patterned fabric images based on GHOG and low-rank decomposition
Chunlei Li, Guangshuai Gao, Zhoufeng Liu +3
In order to accurately detect defects in patterned fabric images, a novel detection algorithm based on Gabor-HOG (GHOG) and low-rank decomposition is proposed in this paper. Defect…