Performance Analysis of Minimum<tex>$ell_1$</tex>-Norm Solutions for Underdetermined Source Separation
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Publication:5354019
DOI10.1109/TSP.2003.822284zbMath1369.94296OpenAlexW1485391971WikidataQ62669648 ScholiaQ62669648MaRDI QIDQ5354019
Ichigaku Takigawa, Jun Toyama, Mineichi Kudo
Publication date: 8 September 2017
Published in: IEEE Transactions on Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1109/tsp.2003.822284
Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Detection theory in information and communication theory (94A13)
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MAP-based underdetermined blind source separation of convolutive mixtures by hierarchical clustering and \(\ell _{1}\)-norm minimization ⋮ Maximum contrast analysis for nonnegative blind source separation ⋮ A Cooperative Recurrent Neural Network for Solving L1 Estimation Problems with General Linear Constraints ⋮ Adaptive blind separation of underdetermined mixtures based on sparse component analysis ⋮ K-hyperline clustering learning for sparse component analysis
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