Blind Source Separation Using Temporal Predictability

DOI10.1162/089976601750265009zbMath1009.62003OpenAlexW2156550040WikidataQ30328369 ScholiaQ30328369MaRDI QIDQ2746412

James V. Stone

Publication date: 6 May 2003

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: http://eprints.whiterose.ac.uk/1430/1/stone.j.w1.pdf

Mathematics Subject Classification ID

Statistical aspects of information-theoretic topics (62B10)

Related Items (15)

A fixed-point algorithm for blind source separation with nonlinear autocorrelation ⋮ Extracting a low-dimensional predictable time series ⋮ Maximum contrast analysis for nonnegative blind source separation ⋮ Hybrid linear and nonlinear complexity pursuit for blind source separation ⋮ Generating feature spaces for linear algorithms with regularized sparse kernel slow feature analysis ⋮ Automatic extraction system for common artifacts in EEG signals based on evolutionary Stone's BSS algorithm ⋮ A Note on Stone's Conjecture of Blind Signal Separation ⋮ A novel algorithm for dynamic factor analysis ⋮ Fast nonlinear autocorrelation algorithm for source separation ⋮ A Complexity Constrained Nonnegative Matrix Factorization for Hyperspectral Unmixing ⋮ Smooth Component Analysis as Ensemble Method for Prediction Improvement ⋮ Blind Signal Deconvolution as an Instantaneous Blind Separation of Statistically Dependent Sources ⋮ Maximization of nonlinear autocorrelation for blind source separation of non-stationary complex signals ⋮ Blind source separation with nonlinear autocorrelation and non-Gaussianity ⋮ On Blind Separability Based on the Temporal Predictability Method

Cites Work

• Randomness and degrees of irregularity.

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