A multiplicative algorithm for convolutive non-negative matrix factorization based on squared euclidean distance
Using the convolutive nonnegative matrix factorization (NMF) model due to Smaragdis, we develop a novel algorithm for matrix decomposition based on the squared Euclidean distance criterion. The algorithm features new formally derived learning rules and an efficient update for the reconstructed nonne...
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Main Authors: | , , |
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Format: | Default Article |
Published: |
2009
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Subjects: | |
Online Access: | https://hdl.handle.net/2134/5706 |
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