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Haupt, Jarvis - Department of Electrical and Computer Engineering, University of Minnesota
Active Sensing Background and Motivation
A Generalized Restricted Isometry Property Jarvis Haupt and Robert Nowak
COMPRESSIVE SAMPLING FOR SIGNAL DETECTION Jarvis Haupt and Robert Nowak
A NYQUIST FOLDING ANALOG-TO-INFORMATION RECEIVER Gerald L. Fudge1
On the Restricted Isometry of Deterministically Subsampled Fourier Matrices
SIGNAL RECONSTRUCTION FROM NOISY RANDOMIZED PROJECTIONS WITH APPLICATIONS TO WIRELESS SENSING
NEW THEORY AND METHODS IN ADAPTIVE AND COMPRESSIVE SAMPLING FOR SPARSE DISCOVERY
Active Learning adapt sensing
Future Directions Agile Sensors and Stylized Applications
Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation
Improved Bounds for Sparse Recovery from Adaptive Measurements
DETECTING SIGNAL STRUCTURE FROM RANDOMLY-SAMPLED DATA Frank A. Boyle(*), Jarvis Haupt(**),Gerald L. Fudge(*), Chen-Chu A.Yeh(*)
1 Adaptive Sensing for Sparse Recovery
To appear in Proc. 42nd Annu. Conf. Information Sciences and Systems (CISS'08), Princeton, NJ, Mar. 19-21, 2008 1 Compressed Channel Sensing
Signal Reconstruction from Noisy Random Projections
Active Sensing and Learning ICASSP 2011, May 23, Prague
arXiv:1001.5311v2[math.ST]27May2010 Distilled Sensing: Adaptive Sampling for
COMPRESSIVE SAMPLING VS. CONVENTIONAL IMAGING Jarvis Haupt and Robert Nowak
Robust Support Recovery Using Sparse Compressive Sensing Matrices
