HIGH-ORDER CONTRASTS FOR SELF-ADAPTIVE SOURCE SEPARATION

DOI<19::AID-ACS384>3.0.CO;2-7 10.1002/(SICI)1099-1115(199601)10:1<19::AID-ACS384>3.0.CO;2-7zbMath0848.94006OpenAlexW2050597764MaRDI QIDQ4883765

Odile Macchi, Eric Moreau

Publication date: 31 October 1996

Full work available at URL: https://doi.org/10.1002/(sici)1099-1115(199601)10:1<19::aid-acs384>3.0.co;2-7

zbMATH Keywords

cumulantscontrast functionself-learningsource separation

Mathematics Subject Classification ID

Stochastic systems and control (93E99) Signal detection and filtering (aspects of stochastic processes) (60G35) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Stochastic learning and adaptive control (93E35) Detection theory in information and communication theory (94A13)

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One-Bit-Matching Conjecture for Independent Component Analysis ⋮ Adaptive Blind Separation with an Unknown Number of Sources ⋮ A Theory for Learning by Weight Flow on Stiefel-Grassman Manifold ⋮ One-Bit-Matching Theorem for ICA, Convex-Concave Programming on Polyhedral Set, and Distribution Approximation for Combinatorics ⋮ Relative gradient based algorithms for general joint diagonalization of complex matrices ⋮ Descent methods for optimization on homogeneous manifolds ⋮ A Generalized Contrast Function and Stability Analysis for Overdetermined Blind Separation of Instantaneous Mixtures ⋮ IVA using complex multivariate GGD: application to fMRI analysis

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