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...

Descripción completa

Detalles Bibliográficos
Autores principales: Iliev, Filip L., Stanev, Valentin G., Vesselinov, Velimir V., Alexandrov, Boian S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
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

Internet

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

Ejemplares similares