2012 - IEEE Fellow For contributions to time-frequency signal processing
The scientist’s investigation covers issues in Algorithm, Time–frequency analysis, Communication channel, Orthogonal frequency-division multiplexing and Electronic engineering. His Algorithm research incorporates elements of MIMO, Filter and Sensor fusion. His studies deal with areas such as Mathematical analysis, Stochastic process, Spectral density, Multidimensional signal processing and Calculus as well as Time–frequency analysis.
His Multidimensional signal processing research is multidisciplinary, incorporating elements of Constant Q transform, Algebra, Harmonic wavelet transform, S transform and Topology. His Communication channel research includes elements of Multiplexing and Estimator. His work carried out in the field of Orthogonal frequency-division multiplexing brings together such families of science as Wireless, Spectral efficiency, Intersymbol interference and Compressed sensing.
His primary areas of investigation include Algorithm, Communication channel, Time–frequency analysis, Estimator and Signal processing. His Algorithm research is multidisciplinary, relying on both Tracking, Signal, Filter and Control theory. The various areas that Franz Hlawatsch examines in his Communication channel study include Electronic engineering and Topology.
His Time–frequency analysis research includes themes of Stochastic process, Speech recognition and Linear system, Mathematical analysis. The study incorporates disciplines such as Ambiguity function and Pure mathematics, Affine transformation in addition to Mathematical analysis. His Estimator study combines topics in areas such as Estimation theory, Applied mathematics and Compressed sensing.
His scientific interests lie mostly in Algorithm, Belief propagation, Tracking, Factor graph and Artificial intelligence. His studies in Algorithm integrate themes in fields like Probability density function, Filter, Wireless sensor network, Clutter and Sensor fusion. His Belief propagation research is multidisciplinary, incorporating perspectives in Message passing, Distributed computing, Probabilistic logic, Multipath propagation and Robustness.
He has researched Factor graph in several fields, including Computational complexity theory, Theoretical computer science and Radar tracker. As part of the same scientific family, he usually focuses on Computer hardware, concentrating on Real-time computing and intersecting with Time–frequency analysis. His Time–frequency analysis study integrates concerns from other disciplines, such as MIMO and Electronic engineering.
Algorithm, Belief propagation, Factor graph, Particle filter and Scalability are his primary areas of study. Franz Hlawatsch studies Algorithm, focusing on Computational complexity theory in particular. His biological study spans a wide range of topics, including Distributed computing, Nonlinear system, Multipath propagation, Monte Carlo method and Robustness.
Franz Hlawatsch interconnects Message passing, Filter and Radar tracker in the investigation of issues within Factor graph. Franz Hlawatsch combines subjects such as Sequential estimation, Mathematical optimization and Ensemble Kalman filter with his study of Particle filter. His Sensor fusion study incorporates themes from Control theory, State, Estimator, Asynchronous communication and Flexibility.
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Linear and quadratic time-frequency signal representations
F. Hlawatsch;G.F. Boudreaux-Bartels.
IEEE Signal Processing Magazine (1992)
Frame-theoretic analysis of oversampled filter banks
H. Bolcskei;F. Hlawatsch;H.G. Feichtinger.
IEEE Transactions on Signal Processing (1998)
Compressive Estimation of Doubly Selective Channels in Multicarrier Systems: Leakage Effects and Sparsity-Enhancing Processing
G. Taubock;F. Hlawatsch;D. Eiwen;H. Rauhut.
IEEE Journal of Selected Topics in Signal Processing (2010)
A compressed sensing technique for OFDM channel estimation in mobile environments: Exploiting channel sparsity for reducing pilots
G. Taubock;F. Hlawatsch.
international conference on acoustics, speech, and signal processing (2008)
Efficient detection algorithms for MIMO channels: a geometrical approach to approximate ML detection
H. Artes;D. Seethaler;F. Hlawatsch.
IEEE Transactions on Signal Processing (2003)
The Wigner distribution : theory and applications in signal processing
W. Mecklenbräuker;F. Hlawatsch.
Wireless Communications Over Rapidly Time-Varying Channels
Franz Hlawatsch;Gerald Matz.
Distributed particle filtering in agent networks: A survey, classification, and comparison
O. Hlinka;F. Hlawatsch;P. M. Djuric.
IEEE Signal Processing Magazine (2013)
Franz Hlawatsch;Franois Auger.
Likelihood Consensus and Its Application to Distributed Particle Filtering
Ondrej Hlinka;Ondrej Slučiak;Franz Hlawatsch;Petar M. Djurić.
IEEE Transactions on Signal Processing (2012)
Profile was last updated on December 6th, 2021.
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