Blind source separation by sparse decomposition in a signal dictionary.
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Nonlinear and noisy extension of independent component analysis: theory and its application to a pitch sensation model.Blind deconvolution of medical ultrasound images: a parametric inverse filtering approachThe utility of data-driven feature selection: re: Chu et al. 2012.Estimating and accounting for tumor purity in the analysis of DNA methylation data from cancer studiesA Removal of Eye Movement and Blink Artifacts from EEG Data Using Morphological Component Analysis.Reactivity of hemodynamic responses and functional connectivity to different states of alpha synchrony: a concurrent EEG-fMRI study.Independent component analysis for brain FMRI does indeed select for maximal independence.Sparse component analysis using time-frequency representations for operational modal analysisAdvances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixtures.Dissecting structure of prion amyloid fibrils by hydrogen-deuterium exchange ultraviolet Raman spectroscopy.Functional brain networks reconstruction using group sparsity-regularized learning.Local dimension-reduced dynamical spatio-temporal models for resting state network estimation.The virtual brain integrates computational modeling and multimodal neuroimaging.Independent component analysis: recent advances.Dictionary learning algorithms for sparse representation.Role of homeostasis in learning sparse representations.Independent components of magnetoencephalography: localization.Network dynamics for optimal compressive-sensing input-signal recovery.The scale of the problem: recovering images of reionization with Generalized Morphological Component AnalysisSparse Models for Computer VisionSparse representation and its applications in micro-milling condition monitoring: noise separation and tool condition monitoringMathematical background for a method on quotient signal decompositionDevelopment of the Audio Enhancement Method by Using the Reflected Signals in the Reverberant EnvironmentResearch on the Sparse Representation for Gearbox Compound Fault Features Using Wavelet BasesThe LOST Algorithm: Finding Lines and Separating Speech MixturesA unified approach to sparse signal processing
P2860
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P2860
Blind source separation by sparse decomposition in a signal dictionary.
description
2001 nî lūn-bûn
@nan
2001 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2001 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2001年の論文
@ja
2001年論文
@yue
2001年論文
@zh-hant
2001年論文
@zh-hk
2001年論文
@zh-mo
2001年論文
@zh-tw
2001年论文
@wuu
name
Blind source separation by sparse decomposition in a signal dictionary.
@ast
Blind source separation by sparse decomposition in a signal dictionary.
@en
type
label
Blind source separation by sparse decomposition in a signal dictionary.
@ast
Blind source separation by sparse decomposition in a signal dictionary.
@en
prefLabel
Blind source separation by sparse decomposition in a signal dictionary.
@ast
Blind source separation by sparse decomposition in a signal dictionary.
@en
P2860
P1433
P1476
Blind source separation by sparse decomposition in a signal dictionary.
@en
P2093
Zibulevsky M
P2860
P304
P356
10.1162/089976601300014385
P577
2001-04-01T00:00:00Z