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» Blind noise variance estimation for OFDMA signals
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ICASSP
2011
IEEE
14 years 3 months ago
Source localization using time difference of arrival within a sparse representation framework
The problem addressed is source localization via time-differenceof-arrival estimation in a multipath channel. Solving this localization problem typically implies cross-correlating...
Ciprian R. Comsa, Alexander M. Haimovich, Stuart C...
IJON
2006
169views more  IJON 2006»
14 years 11 months ago
Denoising using local projective subspace methods
In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE) and Kernel PCA (KPCA). The algorithm LICA relies on app...
Peter Gruber, Kurt Stadlthanner, Matthias Böh...
ICASSP
2009
IEEE
15 years 6 months ago
Independent component analysis for noisy speech recognition
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...
Hsin-Lung Hsieh, Jen-Tzung Chien, Koichi Shinoda, ...
ICASSP
2011
IEEE
14 years 3 months ago
A sliding-window online fast variational sparse Bayesian learning algorithm
In this work a new online learning algorithm that uses automatic relevance determination (ARD) is proposed for fast adaptive nonlinear filtering. A sequential decision rule for i...
Thomas Buchgraber, Dmitriy Shutin, H. Vincent Poor
105
Voted
ICA
2007
Springer
15 years 1 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