What is he best known for?
The fields of study he is best known for:
- Statistics
- Algorithm
- Artificial intelligence
His primary scientific interests are in Algorithm, Estimation theory, Sensor array, Signal processing and Subspace topology.
Mats Viberg has researched Algorithm in several fields, including Weighting, Mathematical optimization and Minimum-variance unbiased estimator.
His Estimation theory research includes elements of Covariance matrix, Parametric statistics, Covariance and Array processing.
His work deals with themes such as Estimator, Signal subspace and Antenna array, which intersect with Sensor array.
His Signal processing study is associated with Signal.
In his research, Transmission is intimately related to Electronic engineering, which falls under the overarching field of Signal.
His most cited work include:
- Two decades of array signal processing research: the parametric approach (3431 citations)
- Sensor array processing based on subspace fitting (616 citations)
- Subspace-based methods for the identification of linear time-invariant systems (519 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Algorithm, Electronic engineering, Sensor array, Signal processing and Estimation theory.
His Algorithm research includes themes of Subspace topology, Estimator, Statistics and Mathematical optimization.
The Electronic engineering study combines topics in areas such as Antenna array, Antenna, MIMO, Radar and Direction finding.
His Sensor array study incorporates themes from Parametric model, Covariance, Beamforming, Artificial intelligence and Pattern recognition.
Signal processing is the subject of his research, which falls under Signal.
The various areas that he examines in his Estimation theory study include Weighting, Signal subspace and Parametric statistics.
He most often published in these fields:
- Algorithm (47.69%)
- Electronic engineering (26.15%)
- Sensor array (23.85%)
What were the highlights of his more recent work (between 2013-2020)?
- Electronic engineering (26.15%)
- Algorithm (47.69%)
- Mathematical optimization (15.38%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Electronic engineering, Algorithm, Mathematical optimization, Estimator and Sensor array.
He studies Beamforming, a branch of Electronic engineering.
His research integrates issues of Sampling, Clutter and Signal generator in his study of Algorithm.
His Estimator study integrates concerns from other disciplines, such as Subspace topology and Direction of arrival.
His research in Sensor array intersects with topics in Ideal, Covariance, Interpolation, Recursive Bayesian estimation and Signal processing.
Mats Viberg focuses mostly in the field of Discretization, narrowing it down to topics relating to Elastic net regularization and, in certain cases, Estimation theory.
Between 2013 and 2020, his most popular works were:
- Simultaneous information and power transfer under a non-linear RF energy harvesting model (42 citations)
- Massive MIMO Systems With IQ Imbalance: Channel Estimation and Sum Rate Limits (23 citations)
- DOA Estimation Methods and Algorithms (17 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Algorithm
- Artificial intelligence
The scientist’s investigation covers issues in Algorithm, Mathematical optimization, Estimator, Electronic engineering and Sensor array.
His primary area of study in Algorithm is in the field of Computational complexity theory.
His studies in Estimator integrate themes in fields like Parametric statistics, Direction of arrival, Rational function, Covariance and Relaxation.
His work carried out in the field of Electronic engineering brings together such families of science as Telecommunications, Coupling and Ideal.
His Emphasis research integrates issues from Beamforming and Signal processing.
He is interested in Array processing, which is a branch of Signal processing.
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