D-Index & Metrics Best Publications
Sergiy A. Vorobyov

Sergiy A. Vorobyov

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Electronics and Electrical Engineering D-index 30 Citations 6,652 138 World Ranking 3574 National Ranking 35

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Algorithm
  • Artificial intelligence

Sergiy A. Vorobyov mainly focuses on Robustness, Algorithm, MIMO, Adaptive beamformer and Mathematical optimization. His research on Robustness often connects related areas such as Channel state information. His Algorithm research is multidisciplinary, relying on both Statistics, Identifiability, Signal subspace and Artificial intelligence.

Sergiy A. Vorobyov interconnects Radar, Signal-to-noise ratio and Control theory in the investigation of issues within MIMO. The Radar study combines topics in areas such as Waveform and Electronic engineering. His Adaptive beamformer study combines topics in areas such as Quadratic programming and Minimum-variance unbiased estimator.

His most cited work include:

  • Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem (1135 citations)
  • Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars (267 citations)
  • Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming (199 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Algorithm, MIMO, Mathematical optimization, Beamforming and Communication channel. His Algorithm research incorporates themes from Subspace topology, Statistics and Signal. His work carried out in the field of MIMO brings together such families of science as Radar, Upper and lower bounds, Continuous-wave radar and Control theory.

His research integrates issues of Mimo radar, Waveform, Electronic engineering and Signal-to-noise ratio in his study of Radar. His Mathematical optimization course of study focuses on Relay and Wireless and Resource allocation. His Beamforming research incorporates elements of Space-time adaptive processing, Wireless sensor network, Sensor array and Robustness.

He most often published in these fields:

  • Algorithm (38.75%)
  • MIMO (26.57%)
  • Mathematical optimization (22.51%)

What were the highlights of his more recent work (between 2018-2021)?

  • Algorithm (38.75%)
  • Radar (14.76%)
  • MIMO (26.57%)

In recent papers he was focusing on the following fields of study:

His main research concerns Algorithm, Radar, MIMO, Adaptive beamformer and Artificial intelligence. The concepts of his Algorithm study are interwoven with issues in Vandermonde matrix, Graph and White noise. He combines subjects such as Waveform and Signal processing with his study of Radar.

His study with MIMO involves better knowledge in Communication channel. His Adaptive beamformer study incorporates themes from Signal-to-noise ratio and Maximization. His studies deal with areas such as Smoothing and Pattern recognition as well as Artificial intelligence.

Between 2018 and 2021, his most popular works were:

  • Toward Millimeter-Wave Joint Radar Communications: A signal processing perspective (82 citations)
  • Adaptive Virtual Waveform Design for Millimeter-Wave Joint Communication–Radar (26 citations)
  • New Designs on MVDR Robust Adaptive Beamforming Based on Optimal Steering Vector Estimation (16 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Artificial intelligence
  • Algorithm

His primary scientific interests are in Algorithm, Radar, MIMO, Signal-to-noise ratio and Applied mathematics. As part of the same scientific family, Sergiy A. Vorobyov usually focuses on Algorithm, concentrating on Subspace topology and intersecting with Maximum likelihood and Array processing. His studies in Radar integrate themes in fields like Extremely high frequency, Waveform and Electronic engineering.

His study in MIMO is interdisciplinary in nature, drawing from both Vandermonde matrix and Signal. His Applied mathematics research integrates issues from Adaptive beamformer, Gradient method, Lipschitz continuity and Relaxation. The various areas that Sergiy A. Vorobyov examines in his Gradient method study include Line search, Optimization problem, Robustness and Rate of convergence.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Robust adaptive beamforming using worst-case performance optimization: a solution to the signal mismatch problem

S.A. Vorobyov;A.B. Gershman;Zhi-Quan Luo.
IEEE Transactions on Signal Processing (2003)

1502 Citations

Phased-MIMO Radar: A Tradeoff Between Phased-Array and MIMO Radars

Aboulnasr Hassanien;Sergiy A Vorobyov.
IEEE Transactions on Signal Processing (2010)

380 Citations

Cognitive radio networks

Xuemin Hong;Zengmao Chen;Cheng-Xiang Wang;S.A. Vorobyov.
IEEE Vehicular Technology Magazine (2009)

266 Citations

Robust Adaptive Beamforming Based on Steering Vector Estimation With as Little as Possible Prior Information

Arash Khabbazibasmenj;S. A. Vorobyov;A. Hassanien.
IEEE Transactions on Signal Processing (2012)

250 Citations

Spectrum Sharing in Wireless Networks via QoS-Aware Secondary Multicast Beamforming

K.T. Phan;S.A. Vorobyov;N.D. Sidiropoulos;C. Tellambura.
IEEE Transactions on Signal Processing (2009)

240 Citations

Transmit Energy Focusing for DOA Estimation in MIMO Radar With Colocated Antennas

A Hassanien;S A Vorobyov.
IEEE Transactions on Signal Processing (2011)

232 Citations

Collaborative beamforming for wireless sensor networks with Gaussian distributed sensor nodes

M.F.A. Ahmed;S.A. Vorobyov.
IEEE Transactions on Wireless Communications (2009)

218 Citations

Blind noise reduction for multisensory signals using ICA and subspace filtering, with application to EEG analysis.

Sergiy A. Vorobyov;Andrzej Cichocki.
Biological Cybernetics (2002)

209 Citations

Principles of minimum variance robust adaptive beamforming design

Sergiy A. Vorobyov.
Signal Processing (2013)

204 Citations

Robust Adaptive Beamforming Using Sequential Quadratic Programming: An Iterative Solution to the Mismatch Problem

A. Hassanien;S.A. Vorobyov;K.M. Wong.
IEEE Signal Processing Letters (2008)

192 Citations

Best Scientists Citing Sergiy A. Vorobyov

Alex B. Gershman

Alex B. Gershman

TU Darmstadt

Publications: 44

Hing Cheung So

Hing Cheung So

City University of Hong Kong

Publications: 35

Guan Gui

Guan Gui

Nanjing University of Posts and Telecommunications

Publications: 35

Wei Liu

Wei Liu

Shanghai Jiao Tong University

Publications: 34

Guisheng Liao

Guisheng Liao

Xidian University

Publications: 33

Wen-Qin Wang

Wen-Qin Wang

University of Electronic Science and Technology of China

Publications: 30

Yimin Zhang

Yimin Zhang

Temple University

Publications: 30

Sofiene Affes

Sofiene Affes

Institut National de la Recherche Scientifique

Publications: 28

Moeness G. Amin

Moeness G. Amin

Villanova University

Publications: 27

Nicholas D. Sidiropoulos

Nicholas D. Sidiropoulos

University of Virginia

Publications: 26

Wee Ser

Wee Ser

Nanyang Technological University

Publications: 24

Emil Bjornson

Emil Bjornson

Royal Institute of Technology

Publications: 22

Bjorn Ottersten

Bjorn Ottersten

University of Luxembourg

Publications: 22

Yingsong Li

Yingsong Li

Harbin Engineering University

Publications: 21

Yushu Zhang

Yushu Zhang

Nanjing University of Aeronautics and Astronautics

Publications: 21

Zhi-Quan Luo

Zhi-Quan Luo

Chinese University of Hong Kong, Shenzhen

Publications: 21

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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