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» RLS-weighted Lasso for adaptive estimation of sparse signals
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ICML
2007
IEEE
14 years 7 months ago
Beamforming using the relevance vector machine
Beamformers are spatial filters that pass source signals in particular focused locations while suppressing interference from elsewhere. The widely-used minimum variance adaptive b...
David P. Wipf, Srikantan S. Nagarajan
NIPS
2007
13 years 7 months ago
Continuous Time Particle Filtering for fMRI
We construct a biologically motivated stochastic differential model of the neural and hemodynamic activity underlying the observed Blood Oxygen Level Dependent (BOLD) signal in Fu...
Lawrence Murray, Amos J. Storkey
CISS
2008
IEEE
14 years 22 days ago
Compressed channel sensing
—Reliable wireless communications often requires accurate knowledge of the underlying multipath channel. This typically involves probing of the channel with a known training wave...
Waheed Uz Zaman Bajwa, Jarvis Haupt, Gil M. Raz, R...
TSP
2008
115views more  TSP 2008»
13 years 6 months ago
Sinusoidal Modeling and Adaptive Channel Prediction in Mobile OFDM Systems
We propose a wireless fading channel prediction algorithm for a pilot-symbol aided Orthogonal Frequency Division Multiplexing (OFDM) system. Assuming a doubly selective (time and ...
Ian C. Wong, Brian L. Evans
ECCV
2008
Springer
14 years 8 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....