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Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals
Factor analysis is broadly used as a powerful unsupervised machine learning tool for reconstruction of hidden features in recorded mixtures of signals. In the case of a linear approximation, the mixtures can be decomposed by a variety of model-free Blind Source Separation (BSS) algorithms. Most of t...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5843288/ https://www.ncbi.nlm.nih.gov/pubmed/29518126 http://dx.doi.org/10.1371/journal.pone.0193974 |