Rigorous optimisation of multilinear discriminant analysis with Tucker and PARAFAC structures

BACKGROUND: We propose rigorously optimised supervised feature extraction methods for multilinear data based on Multilinear Discriminant Analysis (MDA) and demonstrate their usage on Electroencephalography (EEG) and simulated data. While existing MDA methods use heuristic optimisation procedures bas...

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Detalles Bibliográficos
Autores principales: Frølich, Laura, Andersen, Tobias Søren, Mørup, Morten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977741/
https://www.ncbi.nlm.nih.gov/pubmed/29848301
http://dx.doi.org/10.1186/s12859-018-2188-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977741/
https://www.ncbi.nlm.nih.gov/pubmed/29848301
http://dx.doi.org/10.1186/s12859-018-2188-0

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