What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
Christian Jutten mainly investigates Artificial intelligence, Algorithm, Pattern recognition, Blind signal separation and Independent component analysis.
The various areas that he examines in his Artificial intelligence study include Machine learning, Adaptive filter and Computer vision.
His Algorithm research includes elements of Probleme inverse, Matrix and Signal processing.
His Pattern recognition research is multidisciplinary, incorporating elements of Electrocardiography, Covariance matrix and Source separation.
His Blind signal separation research integrates issues from Component analysis, Linear model, Control theory and Electroencephalography.
Christian Jutten usually deals with Independent component analysis and limits it to topics linked to Nonlinear system and Mutual information, Regularization, Mathematical optimization, Gradient method and Mechanics.
His most cited work include:
- Blind separation of sources, Part 1: an adaptive algorithm based on neuromimetic architecture (2228 citations)
- Handbook of Blind Source Separation: Independent Component Analysis and Applications (1091 citations)
- OP-ELM: Optimally Pruned Extreme Learning Machine (609 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Artificial intelligence, Pattern recognition, Algorithm, Blind signal separation and Source separation.
His research in Artificial intelligence intersects with topics in Machine learning, Brain–computer interface and Computer vision.
His Dimensionality reduction study, which is part of a larger body of work in Pattern recognition, is frequently linked to Fetal ecg, bridging the gap between disciplines.
His Algorithm research focuses on Nonlinear system and how it connects with Mixing.
His Blind signal separation research is multidisciplinary, relying on both Independent component analysis, Mutual information, Mathematical optimization, Applied mathematics and Signal processing.
Christian Jutten interconnects Independence and Prior probability in the investigation of issues within Source separation.
He most often published in these fields:
- Artificial intelligence (44.47%)
- Pattern recognition (34.51%)
- Algorithm (31.86%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (44.47%)
- Algorithm (31.86%)
- Pattern recognition (34.51%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Algorithm, Pattern recognition, Blind signal separation and Applied mathematics.
His studies deal with areas such as Machine learning and Brain–computer interface as well as Artificial intelligence.
His study in Algorithm is interdisciplinary in nature, drawing from both Coherence, Penalty method, Signal-to-noise ratio and Mixing.
His studies in Pattern recognition integrate themes in fields like Data point, Preprocessor, Curse of dimensionality and Electroencephalography.
His work carried out in the field of Blind signal separation brings together such families of science as Underdetermined system, Independent component analysis, Polynomial and Nonlinear system.
His Applied mathematics study integrates concerns from other disciplines, such as Mathematical optimization, Estimator, Identifiability and Uniqueness.
Between 2016 and 2021, his most popular works were:
- Transfer Learning: A Riemannian Geometry Framework With Applications to Brain–Computer Interfaces (83 citations)
- Riemannian Procrustes Analysis: Transfer Learning for Brain–Computer Interfaces (43 citations)
- Hyperspectral Image Unmixing With Endmember Bundles and Group Sparsity Inducing Mixed Norms (24 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Machine learning
Christian Jutten mainly focuses on Artificial intelligence, Algorithm, Pattern recognition, Hyperspectral imaging and Pixel.
Christian Jutten has researched Artificial intelligence in several fields, including Superposition principle, Epileptic activity, Riemannian geometry, Machine learning and Local field potential.
His work deals with themes such as Coherence, State variable and Nonlinear system, which intersect with Algorithm.
His Nonlinear system study combines topics in areas such as Linear model, Blind signal separation and Markov chain Monte Carlo.
Christian Jutten has included themes like Independent component analysis, Source separation and Posterior probability, Bayesian probability, Bayesian inference in his Blind signal separation study.
He focuses mostly in the field of Pattern recognition, narrowing it down to matters related to Data point and, in some cases, Procrustes analysis.
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