A general approach for mutual information minimization and its application to blind source separation

DOI10.1016/j.sigpro.2004.11.021zbMath1148.94386OpenAlexW2031252874MaRDI QIDQ956252

Massoud Babaie-Zadeh, Christian Jutten

Publication date: 25 November 2008

Published in: Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sigpro.2004.11.021

zbMATH Keywords

mutual informationindependent component analysis (ICA)blind source separation (BSS)information theoretic learningconvolutive mixturesconvolutive post nonlinear (CPNL) mixturesgradient of mutual informationpost nonlinear (PNL) mixturesscore function difference (SFD)

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Detection theory in information and communication theory (94A13)

Related Items (4)

Some results about kernel estimators for function derivatives based on stationary and ergodic continuous time processes with applications ⋮ Blind separation of instantaneous mixtures of independent/dependent sources ⋮ Estimating the Mixing Matrix in Sparse Component Analysis Based on Converting a Multiple Dominant to a Single Dominant Problem ⋮ Separation of Stellar Spectra Based on Non-negativity and Parametric Modelling of Mixing Operator

This page was built for publication: A general approach for mutual information minimization and its application to blind source separation