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CORR
2011
Springer
148views Education» more  CORR 2011»
14 years 6 months ago
How well can we estimate a sparse vector?
The estimation of a sparse vector in the linear model is a fundamental problem in signal processing, statistics, and compressive sensing. This paper establishes a lower bound on t...
Emmanuel J. Candès, Mark A. Davenport
IPMI
2001
Springer
16 years 18 days ago
Spatio-temporal Covariance Model for Medical Images Sequences: Application to Functional MRI Data
Spatial and temporal correlations which affect the signal measured in functional MRI (fMRI) are usually not considered simultaneously (i.e., as non-independent random processes) in...
Frithjof Kruggel, Habib Benali, Mélanie P&e...

Publication
1851views
17 years 27 days ago
Cerebrovascular Segmentation from TOF Using Stochastic Models
In this paper, we present an automatic statistical approach for extracting 3D blood vessels from time-of-flight (TOF) magnetic resonance angiography (MRA) data. The voxels of the d...
M. Sabry Hassouna, Aly A. Farag, Stephen Hushek, T...
ICASSP
2008
IEEE
15 years 6 months ago
Maximum a posteriori ICA: Applying prior knowledge to the separation of acoustic sources
Independent component analysis (ICA) for convolutive mixtures is often applied in the frequency domain due to the desirable decoupling into independent instantaneous mixtures per ...
Graham W. Taylor, Michael L. Seltzer, Alex Acero
ICASSP
2008
IEEE
15 years 6 months ago
Unsupervised optimal phoneme segmentation: Objectives, algorithm and comparisons
Phoneme segmentation is a fundamental problem in many speech recognition and synthesis studies. Unsupervised phoneme segmentation assumes no knowledge on linguistic contents and a...
Yu Qiao, Naoya Shimomura, Nobuaki Minematsu