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Unsupervised Learning for Monaural Source Separation Using Maximization–Minimization Algorithm with Time–Frequency Deconvolution †
This paper presents an unsupervised learning algorithm for sparse nonnegative matrix factor time–frequency deconvolution with optimized fractional [Formula: see text]-divergence. The [Formula: see text]-divergence is a group of cost functions parametrized by a single parameter [Formula: see text]. T...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5982401/ https://www.ncbi.nlm.nih.gov/pubmed/29702629 http://dx.doi.org/10.3390/s18051371 |