2023 - Research.com Computer Science in Sweden Leader Award
2023 - Research.com Electronics and Electrical Engineering in Sweden Leader Award
2022 - Research.com Computer Science in Sweden Leader Award
2022 - Research.com Electronics and Electrical Engineering in Sweden Leader Award
Fredrik Gustafsson focuses on Control theory, Kalman filter, Particle filter, Algorithm and Artificial intelligence. His research in Control theory intersects with topics in Process, Offset, Bandwidth and Power control. His work deals with themes such as Estimation theory, Nonlinear system, Adaptive filter and Fault detection and isolation, which intersect with Kalman filter.
The Particle filter study combines topics in areas such as Wireless sensor network, Recursive Bayesian estimation, Simulation, Base station and Monte Carlo method. The concepts of his Artificial intelligence study are interwoven with issues in Movement, Gaussian process, Computer vision, Direction information and Pattern recognition. His work carried out in the field of Computer vision brings together such families of science as Inertial navigation system and Signal processing.
Algorithm, Control theory, Artificial intelligence, Kalman filter and Particle filter are his primary areas of study. His study in Algorithm is interdisciplinary in nature, drawing from both Linear system, Mathematical optimization, Filter and System identification. His studies deal with areas such as Noise, Estimator and Power control as well as Control theory.
As a part of the same scientific family, Fredrik Gustafsson mostly works in the field of Artificial intelligence, focusing on Signal processing and, on occasion, Real-time computing. His Kalman filter study frequently links to adjacent areas such as Fault detection and isolation. Fredrik Gustafsson combines subjects such as Monte Carlo method, Gaussian noise and Nonlinear system with his study of Particle filter.
Fredrik Gustafsson focuses on Algorithm, Signal processing, Mathematical optimization, Filter and Real-time computing. His Algorithm research is multidisciplinary, relying on both Smoothing, Estimator, Bayesian probability, Nonlinear system and Noise measurement. His research integrates issues of Kalman filter, Linear system and Benchmark in his study of Nonlinear system.
Extended Kalman filter is the focus of his Kalman filter research. Within one scientific family, he focuses on topics pertaining to Particle filter under Signal processing, and may sometimes address concerns connected to Monte Carlo method and Expectation–maximization algorithm. His Mathematical optimization research integrates issues from Covariance matrix and Applied mathematics.
Fredrik Gustafsson mostly deals with Algorithm, Artificial intelligence, Kalman filter, Nuclear physics and Inertial measurement unit. His Algorithm study combines topics in areas such as Discretization, Gaussian process, Bayesian probability and Metric. His Artificial intelligence study integrates concerns from other disciplines, such as Machine learning, Focus, Cocktail party effect and Pipeline.
His biological study spans a wide range of topics, including Mathematical optimization and Nonlinear system. His Nonlinear system study combines topics from a wide range of disciplines, such as Monte Carlo method, Ensemble Kalman filter and Signal processing. The various areas that Fredrik Gustafsson examines in his Inertial measurement unit study include Dead reckoning and Sensor fusion.
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Particle filters for positioning, navigation, and tracking
F. Gustafsson;F. Gunnarsson;N. Bergman;U. Forssell.
IEEE Transactions on Signal Processing (2002)
Adaptive filtering and change detection
Mobile positioning using wireless networks: possibilities and fundamental limitations based on available wireless network measurements
F. Gustafsson;F. Gunnarsson.
IEEE Signal Processing Magazine (2005)
Marginalized particle filters for mixed linear/nonlinear state-space models
T. Schon;F. Gustafsson;P.-J. Nordlund.
IEEE Transactions on Signal Processing (2005)
Particle filter theory and practice with positioning applications
IEEE Aerospace and Electronic Systems Magazine (2010)
Slip-based tire-road friction estimation
A unifying construction of orthonormal bases for system identification
B. Ninness;F. Gustafsson.
IEEE Transactions on Automatic Control (1997)
Marginalized Particle Filters for Nonlinear State-space Models
Thomas Schön;Fredrik Gustafsson;Per-Johan Nordlund.
On Resampling Algorithms for Particle Filters
Jeroen D. Hol;Thomas B. Schon;Fredrik Gustafsson.
2006 IEEE Nonlinear Statistical Signal Processing Workshop (2006)
Statistical Sensor Fusion
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