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SIAMSC
2011
219views more  SIAMSC 2011»
14 years 4 months ago
Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian
We consider the problem of estimating the uncertainty in large-scale linear statistical inverse problems with high-dimensional parameter spaces within the framework of Bayesian inf...
H. P. Flath, Lucas C. Wilcox, Volkan Akcelik, Judi...
TASLP
2011
14 years 4 months ago
Time-Domain Blind Separation of Audio Sources on the Basis of a Complete ICA Decomposition of an Observation Space
—Time-domain algorithms for blind separation of audio sources can be classified as being based either on a partial or complete decomposition of an observation space. The decompo...
Zbynek Koldovský, Petr Tichavský
JCIT
2010
118views more  JCIT 2010»
14 years 4 months ago
Signal Spectrum Sensing Robust to Noise Uncertainty
Lack of robustness against noise uncertainty is a bottleneck of current spectrum sensing strategies to detect the primary signals. Due to noise uncertainty, the performance of tra...
Zhongbao Chen, Fuliang Bao, Zhigang Fang
MA
2010
Springer
150views Communications» more  MA 2010»
14 years 4 months ago
Cokriging for spatial functional data
This work proposes to generalize the method of cokriging when data are spatially sampled curves. A spatial functional linear model is constructed including spatial dependencies be...
David Nerini, Pascal Monestiez, Claude Manté...
SIAMIS
2010
167views more  SIAMIS 2010»
14 years 4 months ago
Global Solutions of Variational Models with Convex Regularization
Abstract. We propose an algorithmic framework for computing global solutions of variational models with convex regularity terms that permit quite arbitrary data terms. While the mi...
Thomas Pock, Daniel Cremers, Horst Bischof, Antoni...