A Comparative Study of Approximate Joint Diagonalization Algorithms for Blind Source Separation in Presence of Additive Noise

DOI10.1109/TSP.2007.893974zbMath1391.94189MaRDI QIDQ4564667

Serge Dégerine, Elimane Kane

Publication date: 12 June 2018

Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Eigenvalues, singular values, and eigenvectors (15A18)

Related Items (5)

Gradient-based joint block diagonalization algorithms: application to blind separation of FIR convolutive mixtures ⋮ Blind deconvolution of the aortic pressure waveform using the Malliavin calculus ⋮ Multichannel blind deconvolution using the stochastic calculus for the estimation of the central arterial pressure ⋮ Line search and trust region strategies for canonical decomposition of semi-nonnegative semi-symmetric 3rd order tensors ⋮ Householder transform based joint diagonal zero diagonalization for source separation using time-frequency distributions

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