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20102024
most citedA Correlation Analysis Method for Power Systems Based on Random Matrix Theory

82 citations · 620 across the 68 of their papers we have counts for

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Showing 2018 · eess.SPShow all

7 papers · 2 filters

eess.SP2018★ 63 cited

Spatio-Temporal Correlation Analysis of Online Monitoring Data for Anomaly Detection and Location in Distribution Networks

Xin Shi, Robert Qiu, Zenan Ling +3

The online monitoring data in distribution networks contain rich information on the running states of the networks. By leveraging the data, this paper proposes a spatio-temporal co…

eess.SP2018

Unsupervised Feature Learning for Online Voltage Stability Evaluation and Monitoring Based on Variational Autoencoder

Haosen Yang, Robert C. Qiu, Xin Shi +1

With the increase of uncertain elements in power systems and extensive deployment of online monitoring devices, it is necessary to search a more real-time and robust voltage stabil…

eess.SP2018★ 46 cited

Efficient Nonlinear Precoding for Massive MU-MIMO Downlink Systems with 1-Bit DACs

Lei Chu, Fei Wen, Lily Li +1

The power consumption of digital-to-analog converters (DACs) constitutes a significant proportion of the total power consumption in a massive multiuser multiple-input multiple-outp…

eess.SP2018

Shifting Maximum Eigenvalue Detection in Low SNR Environment

Lin Zheng, Robert C. Qiu, Qing Feng +1

Maximum eigenvalue detection (MED) is an important application of random matrix theory in spectrum sensing and signal detection. However, in small signal-to-noise ratio environment…

eess.SP2018★ 1 cited

Eigen-Inference Precoding for Coarsely Quantized Massive MU-MIMO System with Imperfect CSI

Lei Chu, Robert Qiu, Fei Wen

This work considers the precoding problem in massive multiuser multiple-input multiple-output (MU-MIMO) systems equipped with low-resolution digital-to-analog converters (DACs). In…

eess.SP2018★ 1 cited

Improvement of Resting-state EEG Analysis Process with Spectrum Weight-Voting based on LES

Yumeng Ye, Haichun Liu, TianHong Zhang +4

EEG is a non-invasive technique for recording brain bioelectric activity, which has potential applications in various fields such as human-computer interaction and neuroscience. Ho…