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Generalized Alpha-Beta Divergences and Their Application to Robust Nonnegative Matrix Factorization

, , and . Entropy, 13 (1): 134--170 (January 2011)
DOI: 10.3390/e13010134

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Stability analysis of adaptive algorithms for blind source separation of convolutive mixtures, and . Signal Processing, 78 (3): 265--275 (November 1999)The Minimum Entropy and Cumulants Based Contrast Functions for Blind Source Extraction., , and . IWANN (2), volume 2085 of Lecture Notes in Computer Science, page 786-793. Springer, (2001)A Gauss-Newton method for blind source separation of convolutive mixtures., and . ICASSP, page 2093-2096. IEEE, (1998)Improvement of the Initialization of ICA Time-Frequency Algorithms for Speech Separation., , and . ICA, volume 5441 of Lecture Notes in Computer Science, page 629-636. Springer, (2009)Bounded Component Analysis of the training error., , , and . IJCNN, page 1-7. IEEE, (2012)The Complex Version of the Minimum Support Criterion., , and . ICA, volume 4666 of Lecture Notes in Computer Science, page 17-24. Springer, (2007)The Minimum Support Criterion for Blind Signal Extraction: A Limiting Case of the Strengthened Young's Inequality., and . ICA, volume 3195 of Lecture Notes in Computer Science, page 57-64. Springer, (2004)Generalization of an Active Set Newton Algorithm with Alpha-Beta divergences for audio separation., , , and . EUSIPCO, page 306-310. IEEE, (2021)Criterion for signal extraction in underdetermined mixtures of bounded support., , and . Signal Process., 91 (10): 2437-2442 (2011)The Minimum Risk Principle That Underlies the Criteria of Bounded Component Analysis., and . IEEE Trans. Neural Networks Learn. Syst., 26 (5): 964-981 (2015)