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» Estimating random variables from random sparse observations
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ICA
2007
Springer
13 years 10 months ago
Gradient Convolution Kernel Compensation Applied to Surface Electromyograms
Abstract. This paper introduces gradient based method for robust assessment of the sparse pulse sources, such as motor unit innervation pulse trains in the filed of electromyograp...
Ales Holobar, Damjan Zazula
TSP
2008
103views more  TSP 2008»
13 years 8 months ago
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches
Abstract--We present a versatile framework for tractable computation of approximate variances in large-scale Gaussian Markov random field estimation problems. In addition to its ef...
Dmitry M. Malioutov, Jason K. Johnson, Myung Jin C...
TIT
2010
128views Education» more  TIT 2010»
13 years 3 months ago
Shannon-theoretic limits on noisy compressive sampling
In this paper, we study the number of measurements required to recover a sparse signal in M with L nonzero coefficients from compressed samples in the presence of noise. We conside...
Mehmet Akçakaya, Vahid Tarokh
CVPR
1996
IEEE
14 years 10 months ago
MUSE: Robust Surface Fitting using Unbiased Scale Estimates
Despite many successful applications of robust statistics, they have yet to be completely adapted to many computer vision problems. Range reconstruction, particularly in unstructu...
James V. Miller, Charles V. Stewart
ICDM
2009
IEEE
205views Data Mining» more  ICDM 2009»
14 years 3 months ago
Active Selection of Sensor Sites in Remote Sensing Applications
— In a data-mining approach, a model for estimation of Aerosol Optical Depth (AOD) from satellite observations is learned using collocated satellite and groundbased observations....
Debasish Das, Zoran Obradovic, Slobodan Vucetic