Sparse Approximation Signal Detection Professors in Global

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Elias Aboutanios
University of New South Wales Australia
signal detection
signal processing
statistical multidimensional signal processing
array signal processing
radar signal processing
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Ian Wassell
University of Cambridge United Kingdom
sparse representation data
sparse image video coding
signal processing
compressive sensing
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George Moustakides
University of Patras Greece
statistical signal processing
adaptive signal processing
sequential detection
communication signal processing
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Sreeraman Rajan
Carleton University Canada
statistical signal processing
adaptive signal processing
signal processing
compressive sensing
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Oleg Michailovich
University of Waterloo Canada
statistical signal processing
signal processing
compressive sensing
approximation theory
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Omair Ahmad
Concordia University Canada
adaptive signal processing
signal processing
object detection tracking
communication signal processing
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Trac-duy Tran
Johns Hopkins University United States of America
sparse representation
sparse recovery
signal analysis
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P Vaidyanathan
California Institute of Technology United States of America
sparse signal reconstruction
compressive sensing
radar signal processing
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Jan Østergaard
Aalborg University Denmark
statistical signal processing
signal processing
acoustic signal processing
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Mahdi Cheraghchi
Imperial College London United Kingdom
sparse recovery
signal processing
compressive sensing
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Selin Aviyente
Michigan State University United States of America
statistical signal processing
non-stationary signal analysis
signal representation
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James Hopgood
University of Edinburgh United Kingdom
statistical signal processing
single-channel signal separation
multi-channel signal separation
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Heather Wilber
University of Washington United States of America
signal processing
nonlinear approximation methods
approximation theory
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Zoltán Szabó
London School of Economics and Political Science United Kingdom
structured sparsity
statistical machine learning
remote sensing
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Holger Rauhut
Ludwig-Maximilians-Universität München Germany
signal processing
compressive sensing
approximation theory
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Ralf Peeters
Maastricht University Netherlands
signal image processing
statistical parameter estimation
pattern recognition feature extraction
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Daniel Xiang
University of Chicago United States of America
sparse-approximation signal detection
selective inference
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Tatjana Pavlenko
Uppsala University Sweden
sparse signal detection
statistical machine learning
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Tengyao Wang
London School of Economics United Kingdom
sparse signal detection
statistical learning-assisted material discovery
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Giang Tran
University of Waterloo Canada
sparse modeling
sparse optimization methods
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Pierre Vandergheynst
École Polytechnique Fédérale de Lausanne Switzerland
sparse approximations
signal processing
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